CN116279112B

CN116279112B - Engine simulation method, sound wave synthesis method and related devices

Info

Publication number: CN116279112B
Application number: CN202310600578.XA
Authority: CN
Inventors: 朱志鹏; 马峰; 胡明清; 支洪平
Original assignee: Iflytek Suzhou Technology Co Ltd
Current assignee: Iflytek Suzhou Technology Co Ltd
Priority date: 2023-05-25
Filing date: 2023-05-25
Publication date: 2024-01-16
Anticipated expiration: 2043-05-25
Also published as: CN116279112A

Abstract

The application discloses an engine simulation method, a sound wave synthesis method and a related device, wherein the method comprises the following steps: acquiring the pedal depth of a target vehicle electric door and acquiring the running speed of the target vehicle; determining a switching state of a virtual engine of the target vehicle based on the pedal depth and the travel speed; wherein, the switching state is any one of non-switching, upshift switching, downshift switching and accelerator switching; based on the switching state of the virtual engine, the equivalent predicted rotating speed of the virtual engine under the pedal depth and the running speed is obtained, and the accuracy of the automobile engine simulation can be improved by the mode.

Description

Engine simulation method, sound wave synthesis method and related devices

Technical Field

The application relates to the technical field of automobiles, in particular to an engine simulation method, a sound wave synthesis method and a related device.

Background

With the vigorous development of the new energy automobile industry, a new energy driven power system has become one of the important ways of designing the current automobile power system. And because the power system lacks traditional fuel engine cylinder and exhaust physical system, lead to new energy automobile to lack the unrestrained feedback of matching car brand in traditional driving habit in driving process, also influenced driver's immersive driving experience to a certain extent. The engine sound wave simulation aiming at the new energy automobile can improve the driving experience of a driver in the aspect.

The existing engine simulation method is not accurate enough for the engine simulation of the new energy automobile. However, the acoustic wave simulation of new energy automobiles also depends to a great extent on the accuracy of the engine simulation thereof. In view of this, how to improve the accuracy of the new energy automobile engine simulation is a problem to be solved.

Disclosure of Invention

The technical problem that this application mainly solves is to provide an engine simulation method, acoustic wave synthetic method and relevant device, can improve the accuracy of automobile engine simulation.

In order to solve the technical problems, one technical scheme adopted by the application is as follows: there is provided an engine simulation method, the method comprising: acquiring the pedal depth of a target vehicle electric door and acquiring the running speed of the target vehicle; determining a switching state of a virtual engine of the target vehicle based on the pedal depth and the travel speed; wherein, the switching state is any one of non-switching, upshift switching, downshift switching and accelerator switching; based on the switching state of the virtual engine, the predicted rotational speed equivalent to the virtual engine at the pedal depth and the running speed is obtained.

Wherein determining the switching state of the virtual engine of the target vehicle based on the pedal depth and the travel speed includes: determining a motion state of the target vehicle based on the pedal depth and the running speed, and determining an accelerator state of the virtual engine based on the pedal depth; the motion state is any one of acceleration, deceleration and idle speed, the throttle state represents equivalent opening and closing fuel injection quantity of the virtual engine under the pedal depth of the electric door, and the switching state of the virtual engine is determined based on the motion state and the throttle state.

Wherein, based on the motion state and the throttle state, determining a switching state of the virtual engine comprises at least one of: determining that the switching state of the target vehicle is not switching in response to the motion state being deceleration or idling; in response to the motion state being acceleration, a switching state of the virtual engine is determined based on the throttle state.

Wherein determining a switching state of the virtual engine based on the throttle state comprises: based on the switching state determined before the virtual engine, acquiring a first judgment result of the current cycle type of the virtual engine; the first judging result represents whether the virtual engine is in any cycle type of an upshift cycle, a downshift cycle and an accelerator switching cycle at present; and determining the current switching state of the virtual engine based on the first judging result and the throttle state.

Wherein, when the first judgment result indicates that the virtual engine is not currently in any cycle type of the upshift cycle, the downshift cycle and the accelerator switching cycle, determining the current switching state of the virtual engine based on the first judgment result and the accelerator state includes: obtaining a detection result representing whether the state of the accelerator changes; based on the detection result, selecting any one of a second judgment result and a previous pedal depth, and determining the current switching state of the virtual engine; and the second judgment result represents whether the upshift condition and the downshift condition are met.

Wherein, based on the detection result, any one of the second judgment result and the previous pedal depth is selected, and the current switching state of the virtual engine is determined, including at least one of the following: responding to the detection result to represent that the throttle state is unchanged, and determining the current switching state of the virtual engine based on a second judgment result; and responding to the detection result to represent the change of the state of the accelerator, and determining the current switching state of the virtual engine based on the previous pedal depth.

Wherein determining the throttle state of the virtual engine based on the pedal depth comprises: acquiring an average value of pedal depth in a first preset time period before; one of several preset throttle states is selected as the throttle state based on an average of the pedal depths.

Wherein, based on the switching state of the virtual engine, obtaining the virtual engine equivalent predicted rotation speed under the pedal depth and the running speed includes: determining a corresponding period based on the switching state of the virtual engine; based on the throttle state of the virtual engine, obtaining the predicted rotating speed of the virtual engine in the period corresponding to the switching state; the throttle state is determined based on the pedal depth of the electric valve, and represents the equivalent opening and closing fuel injection quantity of the virtual engine corresponding to the pedal depth of the electric valve.

Wherein determining the corresponding period based on the switching state of the virtual engine comprises: according to the switching state of the virtual engine, the upshift switching is carried out, an upshift period with the length of a second preset duration is determined, the upshift period comprises a first upshift stage, a second upshift stage and a third upshift stage, and the third upshift stage is divided into a plurality of time periods; based on the throttle state of the virtual engine, obtaining the predicted rotational speed of the virtual engine in the period corresponding to the switching state comprises the following steps: obtaining the maximum rotating speed of the target vehicle in the currently determined accelerator state, obtaining a first product of the maximum rotating speed and a first upshift coefficient, and interpolating between the maximum rotating speed and the first product to obtain the predicted rotating speed in a first upshift stage; obtaining a first product of the maximum rotation speed and a first upshift coefficient, obtaining a second product of the maximum rotation speed and a second upshift coefficient, and interpolating between the first product and the second product to obtain a predicted rotation speed in a second upshift stage; and sequentially taking each time period in the third upshift stage as a first target time period, predicting the rotation speed of the last time period in the third upshift stage according to the rotation speed of the first target time period, and acquiring the predicted rotation speed of the first target time period based on the predicted rotation speed of the last time period.

Wherein determining the corresponding period based on the switching state of the virtual engine comprises: determining a downshift period with a third preset duration according to the shift state of the virtual engine as downshift shift, wherein the downshift period comprises a first downshift stage and a second downshift stage, and the second downshift stage is divided into a plurality of time periods; based on the throttle state of the virtual engine, obtaining the predicted rotational speed of the virtual engine in the period corresponding to the switching state comprises the following steps: obtaining the minimum rotation speed of the target vehicle in the currently determined throttle state, obtaining a third product of the downshift coefficient and the maximum rotation speed of the target vehicle in the currently determined throttle state, and interpolating between the minimum rotation speed and the third product to obtain the predicted rotation speed in the first downshift stage; and sequentially taking each time period in the second downshift stage as a second target time period, predicting the rotation speed of the last time period in the second downshift stage according to the rotation speed of the second target time period, and acquiring the predicted rotation speed of the second target time period based on the predicted rotation speed of the last time period.

Wherein determining the corresponding period based on the switching state of the virtual engine comprises: determining an accelerator switching period based on an exit condition of the accelerator switching period according to the switching state of the virtual engine as accelerator switching, wherein the accelerator switching period represents switching from an original accelerator state to a target accelerator state, one of the original accelerator state and the target accelerator state is a high accelerator state, and the other is a low accelerator state; based on the throttle state of the virtual engine, obtaining the predicted rotational speed of the virtual engine in the period corresponding to the switching state comprises the following steps: and mapping the running speed in the accelerator switching period into the predicted rotating speed in the accelerator switching period by using a target mapping mode, wherein the target mapping mode is a mapping relation between the running speed and the rotating speed established based on the high accelerator state and the low accelerator state.

Wherein, the mapping the driving speed in the accelerator switching period to the predicted rotation speed in the accelerator switching period by using the target mapping mode comprises: performing convex optimization processing on the difference between the running speed in the accelerator switching period and the speed in the low accelerator state to obtain a speed difference value after the convex optimization processing, obtaining a ratio of the difference between the preset rotating speed in the high accelerator state and the preset rotating speed in the low accelerator state to the difference between the speed in the high accelerator state and the speed in the low accelerator state, multiplying the ratio and the speed difference value after the convex optimization processing to obtain a fourth product, and adding the fourth product and the preset rotating speed in the low accelerator state to obtain the predicted rotating speed in the accelerator switching period.

The method for acquiring the running speed of the target vehicle comprises the following steps that the target vehicle is a test vehicle in bench test, and the running speed of the target vehicle is acquired by the following steps: acquiring the pedal depth of a target vehicle brake; and predicting the running speed according to the pedal depth of the electric door and the brake of the target vehicle.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: provided is a method of synthesizing acoustic waves, the method comprising: obtaining a switching state and a predicted rotating speed of a virtual engine of the target vehicle based on the pedal depth and the running speed of an electric door of the target vehicle; the switching state and the predicted rotating speed are obtained based on the engine simulation method in any one of the above; and synthesizing to obtain the sound wave data of the target vehicle based on the switching state and the predicted rotating speed.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: the device comprises an acquisition module, a determination module and a prediction module, wherein the acquisition module is used for acquiring the pedal depth of a target vehicle electric door and acquiring the running speed of the target vehicle; the determining module is used for determining the switching state of the virtual engine of the target vehicle based on the pedal depth and the running speed; wherein, the switching state is any one of non-switching, upshift switching, downshift switching and accelerator switching; the prediction module is used for obtaining the equivalent predicted rotating speed of the virtual engine under the pedal depth and the running speed based on the switching state of the virtual engine.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: the device comprises a prediction module and a synthesis module, wherein the prediction module is used for obtaining the switching state and the predicted rotating speed of a virtual engine of a target vehicle based on the pedal depth and the running speed of an electric door of the target vehicle; the switching state and the predicted rotating speed are obtained based on the engine simulation device; the synthesizing module is used for synthesizing and obtaining the sound wave data of the target vehicle based on the switching state and the predicted rotating speed.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: an electronic device is provided, including a memory and a processor coupled to each other, the processor configured to execute program data stored in the memory, to implement any one of the engine simulation method or the acoustic wave synthesis method.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: the vehicle at least comprises a vehicle body and intelligent equipment carried on the vehicle body, wherein the intelligent equipment is the electronic equipment.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: there is provided a computer readable storage medium having stored thereon program data which when executed by a processor implements any of the engine simulation methods or the acoustic wave synthesizing method described above.

According to the scheme, the pedal depth and the running speed of the electric door of the target vehicle are utilized to determine the switching state of the virtual engine of the target vehicle, the equivalent predicted rotating speed of the virtual engine under the pedal depth and the running speed is obtained based on the switching state of the virtual engine, wherein the switching state is any one of non-switching, upshift switching, downshift switching and accelerator switching, on one hand, the running state of the target vehicle is accurately represented by utilizing the pedal depth and the running speed in the process of engine simulation, the accuracy of engine simulation is improved, on the other hand, the switching state of the virtual engine is obtained, the working state of the virtual engine of the target vehicle is further represented, and further the predicted rotating speed is determined based on the switching state of the virtual engine, and the accuracy of engine simulation is improved.

Drawings

FIG. 1 is a flow chart of an embodiment of an engine simulation method of the present application;

FIG. 2 is a flow chart of another embodiment of step S120 of the present application;

FIG. 3 is a flowchart illustrating another embodiment of step S222 of the present application;

FIG. 4 is a flowchart illustrating a step S222 according to another embodiment of the present application;

FIG. 5 is a flowchart illustrating another embodiment of step S130 of the present application;

FIG. 6 is a flow chart of a further embodiment of step S130 of the present application;

FIG. 7 is a flow chart of a further embodiment of step S130 of the present application;

FIG. 8 is a flow chart of a further embodiment of step S130 of the present application;

FIG. 9 is a flow chart of yet another embodiment of the engine simulation method of the present application;

FIG. 10 is a schematic flow chart of an embodiment of a method of synthesizing acoustic waves according to the present application;

FIG. 11 is a schematic flow chart of another embodiment of the acoustic wave synthesis method of the present application;

FIG. 12 is a schematic flow chart of yet another embodiment of the acoustic wave synthesis method of the present application;

FIG. 13 is a schematic diagram of a framework of one embodiment of an engine simulation apparatus of the present application;

FIG. 14 is a schematic view of a frame of an embodiment of the apparatus for synthesizing acoustic waves of the present application;

FIG. 15 is a schematic diagram of a frame of an embodiment of an electronic device of the present application;

FIG. 16 is a schematic diagram of a framework of one embodiment of a computer-readable storage medium of the present application;

FIG. 17 is a schematic diagram of a frame of an embodiment of a vehicle of the present application.

Detailed Description

In order to make the objects, technical solutions and effects of the present application clearer and more specific, the present application will be further described in detail below with reference to the accompanying drawings and examples. In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, interfaces, techniques, etc., in order to provide a thorough understanding of the present application.

The term "and/or" is herein merely an association relationship describing an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship. Further, "a plurality" herein means two or more than two. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.

Referring to fig. 1, fig. 1 is a flow chart illustrating an embodiment of an engine simulation method of the present application. Specifically, the method may comprise the steps of:

Step S110: the pedal depth of the electric door of the target vehicle is acquired, and the running speed of the target vehicle is acquired.

It should be noted that, the engine simulation method provided in the present application may be applied to a target vehicle, where the target vehicle may be a new energy vehicle (such as an electric car, a hydrogen energy vehicle, etc.) and is used to obtain equivalent working information of a virtual engine corresponding to the target vehicle, where, compared to a fuel vehicle, a new energy vehicle such as an electric car has corresponding changes in terms of power structure, etc., the virtual engine is a relevant component of the new energy vehicle for simulating the power structure of the fuel vehicle, and may, for example, include, but not limited to, a virtual engine, a virtual gearbox, etc., where the former is used to simulate an engine of the fuel vehicle, the latter is used to simulate a gearbox of the fuel vehicle, and other cases may be similarly taken herein without being limited to examples. For example, for a certain electric automobile, equivalent operation information of a virtual engine corresponding to current running information of the electric automobile can be obtained through engine simulation.

Further, the equivalent operation information of the virtual engine obtained by the engine simulation method may be used in processing work related to the target vehicle, for example, may be used for performing engine sound wave simulation, comparing the target vehicle with the fuel vehicle, as a reference for data processing related to the target vehicle, and the like.

It should be noted that the engine simulation may be applied to a real vehicle operation scene, or may also be applied to a bench test or an offline simulation scene.

In a real vehicle operation scenario, the pedal depth and travel speed of the electric door of the target vehicle may be obtained for the acquisition of the target vehicle. Specifically, it may be acquired from bus information of the target vehicle.

In the bench test or the off-line simulation scenario, the target vehicle is a test vehicle at the bench test, and the running speed of the target vehicle may be predicted based on the pedal depth of the brake and the pedal depth of the electric door of the target vehicle.

Taking a real vehicle running scene as an example for explanation, a fixed first preset duration can be preset as a unit duration of engine simulation, a time period with the length of the first preset duration before the current moment can be used as a current time period, the pedal depth and the running speed of an electric door in the current time period are obtained in the running process of a target vehicle, and the switching state of a virtual engine of the target vehicle in the current time period is determined, so that the equivalent predicted rotating speed of the virtual engine in the current time period is obtained.

Further, the pedal depth and the running speed of the electric door of the target vehicle may be obtained by sampling at certain frequency intervals, and the unit duration may have a plurality of sampling points. Accordingly, the predicted rotational speed may include the predicted rotational speeds of the several sampling points, respectively, within the current time period. It should be noted that, the first preset duration may be a duration corresponding to one audio frame, so as to obtain a predicted rotation speed equivalent to a time point of a virtual engine of the target vehicle in the time period, and then the predicted rotation speed may be used to synthesize sound wave data corresponding to one audio frame.

In an application scenario of real vehicle operation, the target vehicle may be collected in terms of a pedal depth and a running speed according to a preset sampling frequency, for example, the running speed and the pedal depth of the electric door are collected at each sampling point, so as to form sequence data.

The running speed and the pedal depth are discrete sequences, and can have the same target length, namely, a plurality of sampling points in the same time period are acquired, wherein the sequence length refers to the number of elements contained in the sequence data, and the sequence length is the same as the number of the sampling points contained in the time period and can be any positive integer. Further, elements at the same position in different sequences are acquired at the same sampling point. For example, the running speed, the first depth of the electric door pedal and the second depth of the brake pedal are respectively collected at n sampling points in a period of time to obtain three sequences of data with the length of n, wherein the sequence one is a running speed data sequence and comprises A ₁ 、A ₂ 、A ₃ 、…、A _n The second sequence is a first depth sequence of the electric door pedal, comprising B ₁ 、B ₂ 、B ₃ 、…、B _n Sequence three is a second depth sequence of brake pedal, comprising C ₁ 、C ₂ 、C ₃ 、…、C _n Wherein elements at the same position in different sequences are acquired at the same sampling point, for example, A ₁ 、B ₁ And C ₁ Are acquired at the same sampling point.

In a specific application scenario, the driving information of the target vehicle may be acquired within a period of 120ms-300ms, the sampling frequency may be set to 8kHz, the sequence length is recorded as L, and the value of L may be between 960-2400. Further, L may typically take on values of 1024 or 2048.

Step S120: based on the pedal depth and the travel speed, a switching state of the virtual engine of the target vehicle is determined.

The switching state is any one of non-switching, upshift switching, downshift switching and accelerator switching. In this embodiment, the virtual engine may include a virtual engine and a virtual gearbox, and the switching state indicates whether the virtual engine has a upshift or a throttle switching. The upshift switching indicates that the virtual engine is changed from a low gear to a high gear, the downshift switching indicates that the virtual engine is changed from a high gear to a low gear, the throttle switching indicates that the throttle state of the virtual engine is changed, the throttle state indicates the equivalent opening and closing fuel injection quantity of the virtual engine, the throttle state can be one of a plurality of preset throttle states, and the throttle state does not switch to indicate that the virtual engine does not have an elevating gear or does not have a throttle switching.

In a specific application scenario, the switching state may be set to a value range of 0, 1, 2, and 3, which respectively correspond to no-switching, upshift switching, downshift switching, and accelerator switching.

Step S130: based on the switching state of the virtual engine, the predicted rotational speed equivalent to the virtual engine at the pedal depth and the running speed is obtained.

The switching state of the virtual engine can represent the assumed operation state of the virtual engine corresponding to the target vehicle from the aspect of whether the up-down gear or the accelerator switching exists, and the operation state of the virtual engine has an association relationship with the switching state of the virtual engine, so that in the process of simulating the virtual engine to obtain the predicted rotating speed, the accuracy of engine simulation can be improved by taking the switching state into consideration of simulation.

In some embodiments, the corresponding period may be determined based on the switching state of the virtual engine, and the predicted rotational speed of the virtual engine in the period corresponding to the switching state may be predicted. Of course, the above examples are only possible implementation manners in practical applications, and based on the foregoing implementation manners, the examples may be reasonably changed according to specific requirements of the practical applications, so as to adapt to the practical requirements. For example, the running speed may be mapped to the rotation speed by a preset mapping manner, and then the rotation speed of each time period may be adjusted according to the switching state.

According to the scheme, on one hand, the running state of the target vehicle is accurately represented by the pedal depth and the running speed in the process of engine simulation, so that the accuracy of engine simulation is improved, on the other hand, the switching state of the virtual engine is obtained, the working state of the virtual engine of the target vehicle is further represented, and further, the accuracy of engine simulation is improved by determining the predicted rotating speed based on the switching state of the virtual engine.

Referring to fig. 2, fig. 2 is a flowchart illustrating another embodiment of step S120 of the present application. Specifically, step S120 may include the steps of:

step S221: the motion state of the target vehicle is determined based on the pedal depth and the travel speed, and the throttle state of the virtual engine is determined based on the pedal depth.

The motion state represents a basic state of the whole vehicle running and can be any one of acceleration, supervision and idling. The throttle state characterizes the equivalent opening and closing fuel injection quantity of the virtual engine under the pedal depth of the electric valve, and the throttle state can be any one of a plurality of preset states.

In a specific application scenario, the motion state may be set to a value range of 0, 1, and 2, corresponding to the running states of the whole vehicle for idle speed, acceleration, and deceleration, respectively.

In a specific application scenario, the throttle state represents the equivalent opening and closing fuel injection quantity percentage of the virtual fuel engine corresponding to the pedal depth of the electric valve, and the equivalent opening and closing fuel injection quantity percentage is set to be in the range of 0, 1, 2, 3, 4 and 5, and corresponds to the pedal depth of the electric valve and the change range of the virtual fuel injection quantity from low to high respectively, and the throttle state is in a total of 6-gear preset state.

It should be noted that the pedal depth/running speed of the electric door includes the pedal depth/running speed of the electric door corresponding to the plurality of sampling points in the current time period. For the current time period, the motion state corresponding to the current time period can be determined based on the pedal depth and the running speed of the electric door at a plurality of sampling points in the time period. The throttle status of the virtual engine during the time period may be determined based on the pedal depth for each of the plurality of sample points during the time period.

In some embodiments, determining the throttle state of the virtual engine based on the pedal depth may include: and acquiring an average value of the pedal depth in a first preset time period before, and selecting one of a plurality of preset throttle states as the throttle state of the virtual engine based on the average value of the pedal depth.

It is understood that the first preset duration may be a unit duration, that is, one of the preset throttle states is determined as the throttle state of the virtual engine in the current time period according to an average value of the pedal depths in the current time period.

In a specific application scenario, the pedal depth is expressed in percentage form, and the throttle status of the virtual engine can be determined by the following formula:

wherein,indicating throttle status->The average value of the pedal depth of the electric gate in the first preset time period is calculated according to the percentage, and the value of the pedal depth of the electric gate in the first preset time period is calculated according to the percentage.

In some embodiments, determining the motion state of the target vehicle based on the pedal depth and the travel speed may include: determining whether the pedal depth of the electric door is greater than zero or equal to zero, determining the motion state of the target vehicle as acceleration in response to the pedal depth of the electric door being greater than zero, determining whether the running speed is greater than zero or equal to zero in response to the pedal depth of the electric door being equal to zero, determining the motion state of the target vehicle as deceleration in response to the running speed being greater than zero, and determining the motion state of the target vehicle as idle in response to the running speed being less than zero. The pedal depth of the electric door may be an average value of pedal depths in a current time period, and the running speed may be an average value of running speeds in the current time period.

In a specific application scenario, when the electric pedal=0% and the real-time speed is >0, the motion state corresponds to deceleration, characterized by a value of 2, when the electric pedal=0% and the real-time speed is=0, the motion state corresponds to idling, characterized by a value of 0, and when the electric pedal is >0%, the motion state corresponds to acceleration, characterized by a value of 1.

Step S222: based on the motion state and the throttle state, a switching state of the virtual engine is determined.

It can be understood that the switching state of the virtual engine is a representation of the working state of the virtual engine, and the motion state and the throttle state of the virtual engine reflect the working state of the virtual engine, so that the switching state of the virtual engine can be determined based on the motion state and the throttle state.

In the above manner, the motion state is obtained by using the pedal depth and the running speed, and the accelerator state is obtained by using the pedal depth. The switching state of the virtual engine can be more accurately determined by combining the information of the basic state of the whole vehicle running represented by the motion state and the vehicle running power condition represented by the pedal depth.

Of course, the above examples are only possible implementation manners in practical applications, and based on the foregoing implementation manners, the examples may be reasonably changed according to specific requirements of the practical applications, so as to adapt to the practical requirements. For example, the switching state of the virtual engine is a representation of the working state of the virtual engine, and other relevant parameters representing the working state of the virtual engine, such as the pedal depth of a brake pedal, the relevant attribute of a vehicle, the running road condition and the like, can be added, and the switching state of the virtual engine of the target vehicle can be determined by combining the pedal depth and the running speed of an electric door.

Referring to fig. 3, fig. 3 is a flowchart illustrating another embodiment of step S222 of the present application. Specifically, step S222 may include the steps of:

step S3221: and judging whether the motion state is acceleration, deceleration or idle speed.

In order to determine the switching state of the virtual engine, it may be determined whether the motion state is acceleration, deceleration, or idle, step S3222 may be executed in response to the motion state being deceleration or idle, and step S3223 may be executed in response to the motion state being acceleration.

Step S3222: the switching state of the target vehicle is determined to be not switching.

In the present embodiment, when the target vehicle is decelerating or idling, it is considered that the target vehicle does not have a switching state in which the upshift or downshift is performed, and it is possible to determine that the switching state is not switching.

Step S3223: based on the throttle state, a switching state of the virtual engine is determined.

In addition, in the case where the motion state in the current period is acceleration, there may be a upshift or a throttle switch. And in response to the motion state being acceleration, judging whether the lifting gear or the accelerator switching exists in the current time period based on the accelerator state.

According to the mode, the switching state can be conveniently and directly determined under the conditions of deceleration and idling, and under the condition of acceleration, the switching state is accurately determined according to the throttle state characteristics of different switching states, so that the simulation accuracy of the virtual engine is improved.

Of course, the above examples are only possible implementation manners in practical applications, and based on the foregoing implementation manners, the examples may be reasonably changed according to specific requirements of the practical applications, so as to adapt to the practical requirements. For example, other related parameters representing the working state of the virtual engine can be added, and the related parameters can be used for determining the switching state of the virtual engine, such as the running speed, the running road condition and the like, along with the motion state and the throttle state.

Referring to fig. 4, fig. 4 is a flowchart illustrating a further embodiment of step S222 of the present application. Specifically, step S222 may include the steps of:

step S4221: and judging whether the motion state is acceleration, deceleration or idle speed.

In order to determine the switching state of the virtual engine, it may be determined whether the motion state is acceleration, deceleration, or idle, and step S4222 may be performed in response to the motion state being deceleration or idle, and steps S4223-S4224 may be performed in response to the motion state being acceleration. Step S3223 may be implemented through steps S4223-S4224.

Step S4222: the switching state of the target vehicle is determined to be not switching.

The description of step S4222 may refer to the foregoing related content of step S3222, and will not be described herein.

Step S4223: and acquiring a first judgment result of the current cycle type of the virtual engine based on the switching state determined before the virtual engine.

The cycle type is matched with the shift state, and the upshift is taken as an example for explanation, the upshift is from a low gear to a high gear, for example, from 1 gear to 2 gears, the process of the shift can be called an upshift cycle, the downshift and the accelerator switch are the same, the downshift corresponds to the downshift cycle, and the accelerator switch corresponds to the accelerator switch cycle.

In this embodiment, the second preset duration may be preset as the duration of the upshift period, the third preset duration may be preset as the duration of the downshift period, and the user may adjust the second preset duration and the third preset duration according to actual needs. In the accelerator switching, the period from the switching state to the accelerator switching state satisfying the accelerator switching period exit condition may be the accelerator switching period by setting the accelerator switching period exit condition in advance.

The first judging result can be used for representing whether the virtual engine is in any period type of an upshift period, a downshift period and an accelerator switching period. The switching state in the current time period indicates whether the virtual fuel engine has a lifting gear or a throttle switch in the current time period. If the switching state of the virtual engine before is either the up-down gear or the accelerator switching, and the virtual engine is still in the corresponding period in the current time period, the switching state of the virtual engine in the current time period can be directly determined. Specifically, if the switching state of the virtual engine determined in the previous period is an upshift switching, the virtual engine may be considered to be in an upshift period within a second preset period from the previous period, so that it may be determined whether the virtual engine is currently in any of the upshift period, the downshift period, and the throttle switching period according to the switching state determined before the virtual engine.

Step S4224: and determining the current switching state of the virtual engine based on the first judging result and the throttle state.

Specifically, based on the first determination result, it may be determined whether the virtual engine is currently in any cycle type of the upshift cycle, the downshift cycle, and the throttle switching cycle, and if the virtual engine is already in any type of the above, the current switching state of the virtual engine, that is, the switching state in the current time period, is consistent with the current cycle.

If it is determined that the virtual engine is not currently in any cycle type based on the first determination result, the current switching state of the virtual engine can be further determined based on the throttle state.

In some embodiments, when the first determination result indicates that the virtual engine is not currently in any cycle type of the upshift cycle, the downshift cycle, and the accelerator switching cycle, the current switching state of the virtual engine may be determined by: and acquiring a detection result representing whether the accelerator state is changed, and selecting any one of a second judgment result and a previous pedal depth based on the detection result to determine the current switching state of the virtual engine, wherein the second judgment result represents whether an upshift condition and a downshift condition are met.

The step of determining whether the accelerator state is changed is to determine whether the accelerator state in the current time period is changed compared with the accelerator state in the previous time period. The detection result can represent that the throttle state in the current time period is changed or not changed compared with the throttle state in the previous time period. The previous pedal depth refers to the pedal depth before the current time. In some embodiments, the previous pedal depth may be the pedal depth of the previous time period. In some embodiments, the throttle state associated with the pedal depth presence may also be used to determine the current switching state of the virtual engine.

Further, based on the detection result, selecting any one of the second determination result and the previous pedal depth, determining the current switching state of the virtual engine includes: and determining the current switching state of the virtual engine based on the second judging result in response to the fact that the throttle state is unchanged, and determining the current switching state of the virtual engine based on the previous pedal depth in response to the fact that the throttle state is changed.

In a specific application scenario, the detection result may be obtained by detecting whether the throttle state stateThrottle [ i ] in the current time period is consistent with the throttle state stateThrottle [ i-1] in the previous time period.

It can be understood that if the detection result indicates that the accelerator state is unchanged, the switching state of the virtual engine is not accelerator switching, then whether an upshift condition and a downshift condition are satisfied is determined according to the second determination result, if the upshift condition is satisfied, the switching state is upshift, if the downshift condition is satisfied, the switching state is downshift, and if the upshift condition and the downshift condition are not satisfied, the switching state is not switch.

The upshift/downshift is to represent a shift change, and a user may preset a plurality of preset throttle states and gear numbers according to actual needs, and through effect adjustment, preset maximum speeds that may be reached by each throttle state in different gears. The current gear of the target vehicle and whether a lifting gear exists or not are determined based on the running speed of the target vehicle and the corresponding throttle state and the maximum speed in the gear.

In a specific application scenario, given that the value of a specific throttle state (statespeed) is 0-5, the maximum speed max_speed [ statespeed ] [ stateGear ] that can be achieved in different gears respectively is the value range of the gear state (stateGear), that is, the gear number of a typical vehicle is 5 gears or 6 gears in total, for example, when the parameter max_speed [5] [0:6] = [0,0.1,0.2,0.4,0.6,0.8,1.0] is set, the maximum speed that can be achieved in each virtual gear 1-6 gears is 0.1,0.2,0.4,0.6,0.8,1.0 times of the maximum design speed of the vehicle.

In some embodiments, the upshift condition includes a travel speed increase and the travel speed exceeds a throttle state and a maximum speed in a previous gear. Further specifically, it may be that the running speed of the current period is greater than the running speed of the previous period, and the running speed of the current period exceeds the maximum speed corresponding to the throttle state of the current period and the gear of the previous period.

In some embodiments, the downshift condition includes a decrease in travel speed, and the travel speed is lower than a maximum speed in a throttle state and a next gear of a previous gear. Further specifically, it may be that the running speed of the current period is smaller than the running speed of the previous period, and the formal speed of the current period is smaller than the accelerator state of the current period and the maximum speed corresponding to the next gear of the previous period.

The condition of accelerator state change can occur in the process of accelerator switching and initializing upshift, so that if the detection result represents the accelerator state change, the accelerator switching and the initializing upshift can be distinguished through the previous pedal depth. Specifically, if the previous pedal depth is zero, the vehicle is initially upshifted, and it is possible to determine that the shift state is upshift, and if the previous pedal depth is not zero, it is determined that the shift state is accelerator. The previous pedal depth may be the pedal depth of the previous period, that is, the pedal depth of all sampling points in the previous period, and further, the average value, the maximum value, the minimum value, and the like of the pedal depths of all sampling points in the previous period.

In some embodiments, the throttle state associated with the pedal depth may also be utilized to determine the switch state. Specifically, if the previous accelerator state is zero, the vehicle is initially upshifted, and it is possible to determine that the switching state is upshifted, and if the previous accelerator state is not zero, it is determined that the switching state is accelerator. The previous throttle state may be the throttle state of the previous period.

Of course, the above examples are only possible implementation manners in practical applications, and based on the foregoing implementation manners, the examples may be reasonably changed according to specific requirements of the practical applications, so as to adapt to the practical requirements. For example, the current switching state of the virtual engine is comprehensively determined by combining the first judgment result and the throttle state without distinguishing the first judgment result.

In a specific application scenario, the virtual engine equivalent predicted rotational speed is obtained by a simulation system of the virtual engine. The simulation system of the virtual engine comprises a real-time state machine maintenance module, wherein the real-time state machine maintenance module comprises a motion state machine, an accelerator state machine and a switching state machine, the motion state machine represents a basic state of the whole vehicle operation, the accelerator state machine represents the opening and closing fuel injection quantity percentage of the virtual fuel engine corresponding to the depth of an electric valve pedal, and the switching state machine represents whether the virtual fuel engine has lifting gear or accelerator switching. In a real-vehicle operation scene, a pedal depth and a real-time travel speed of an electric door of a target vehicle are acquired in real time as inputs, a current motion state of the target vehicle is determined based on the pedal depth and the travel speed, and an accelerator state is determined based on the pedal depth. And then judging whether the current motion state is acceleration, deceleration or idle speed, and determining that the current switching state of the target vehicle is not to be switched in response to the motion state being deceleration or idle speed. And responding to the motion state as acceleration, acquiring a first judging result of the period type where the virtual engine is currently located based on the switching state determined before the virtual engine, and determining that the switching state corresponds to the period type under the condition that the first judging result represents that the virtual engine is currently located in any one of an upshift period, a downshift period and an accelerator switching period. And under the condition that the first switching result represents that the virtual engine is not in any one of an upshift period, a downshift period and an accelerator switching period currently, acquiring a detection result representing whether the accelerator state is changed, judging whether upshift conditions and downshift conditions are met or not according to the fact that the detection result represents that the accelerator state is unchanged, if yes, determining that the switching state is corresponding upshift/downshift, if not, determining that the switching state is not switching, responding to the detection result representing the accelerator state change, judging whether the depth of a pedal before is zero, if zero, determining that the switching state is upshift switching, and if not, determining that the switching state is accelerator switching.

In some embodiments, the real-time state machine maintenance module further includes a gear state machine, which characterizes an equivalent working gear of the virtual engine, and the range of values is 0-6, corresponding to N gear and 1-6 gear of the virtual engine, respectively. The determination of the gear state may be based on the maximum speed max_speed that can be reached by the different gears for a given throttle state (stateThrottle), respectively.

Referring to fig. 5, fig. 5 is a flowchart illustrating another embodiment of step S130 of the present application.

Specifically, step S130 may include:

step S531: based on the switching state of the virtual engine, a corresponding period is determined.

Wherein the cycle type matches the switching state. For the case that the switching state is not switched, the current time period may be considered as a corresponding period, and the predicted rotational speed in the period may be predicted, specifically, the running speed in the current time period may be mapped to the predicted rotational speed by adopting a preset mapping manner.

Step S532: and obtaining the predicted rotating speed of the virtual engine in the period corresponding to the switching state based on the throttle state of the virtual engine.

The throttle state is determined based on the depth of the electric valve pedal, and represents the equivalent opening and closing fuel injection quantity of the virtual engine corresponding to the depth of the electric valve pedal. It will be appreciated that for upshift, downshift, and throttle, the respective periods may be determined. In the period corresponding to the three switching states, the predicted rotational speed is associated with the throttle state of the virtual engine in the current period, so the predicted rotational speed in the corresponding period is predicted based on the throttle state of the virtual engine.

According to the scheme, the switching state of the virtual engine is obtained based on the pedal depth and the running speed, the working state of the virtual engine of the target vehicle is further represented, further, the predicted rotating speed is determined based on the switching state of the virtual engine, the accuracy of engine simulation is improved, further, according to the characteristics of the switching process, the corresponding period is determined based on different switching states, the rotating speed in the switching period is predicted by adopting a scheme different from a preset mapping mode, and therefore the accuracy of virtual engine switching process simulation is improved, and the accuracy of virtual engine simulation is improved.

Referring to fig. 6, fig. 6 is a flowchart illustrating a further embodiment of step S130 of the present application. Specifically, step S130 may include:

step S631: and determining an upshift period with the length of a second preset duration according to the upshift switching state of the virtual engine.

The related description of step S631 may refer to the related content described previously with respect to step S531, and the related descriptions of steps S632 to S634 may refer to the related content described previously with respect to step S532. The second preset time period is predetermined and can be adjusted according to the actual needs of the user. The upshift cycle includes a first upshift stage, a second upshift stage, and a third upshift stage, which may be divided into a plurality of time periods, each of which is a unit duration.

In a specific application scenario, during upshifting, the engine speed is reduced linearly and steadily over time (T _fall ) Then rapidly rises again in a short time (T _attack ) Then gradually and smoothly rises to the corresponding rotation speed (T _spike ). Correspondingly, the upshift period is:

wherein T is _upgear For upshift period, T _fall 、T _attack 、T _spike The first upshift stage, the second upshift stage and the third upshift stage are respectively. The duration of the first upshift phase, the second upshift phase and the third upshift phase may also be predetermined and may be adjusted according to the actual situation.

When in a specific gear or throttle switching state cycle, due to the presence of main reducer conduction, different size driven gear engagement switching, power output and torque variation adjustment, dynamic adjustment considering wheel states, etc. in a real fuel engine, however, when a gear shifting process is described by using physical model modeling, it is often impossible to describe all the characteristics of the whole vehicle power system completely and accurately, which means that the transient of the engine speed is usually included in the gear shifting cycle. To illustrate an application of the predicted rotational speed to the synthesis of the acoustic waves, the transient may cause a defect that may significantly mutate the effect of simulating the engine acoustic waves, and the above problem may be overcome by determining the switching period and correcting or smoothing the rotational speed data of the switching process for the purpose of beautifying the synthesized acoustic wave.

Step S632: and obtaining the maximum rotating speed of the target vehicle in the currently determined accelerator state, obtaining a first product of the maximum rotating speed and the first upshift coefficient, and interpolating between the maximum rotating speed and the first product to obtain the predicted rotating speed in the first upshift stage.

In this embodiment, the highest rotational speed and the lowest rotational speed that can be achieved in different throttle states with a configurable parameter are claimed, and the corresponding formulas are expressed as follows:

wherein i represents the throttle state, in the formulaFor configurable parameters, ++>Indicating the maximum rotational speed achievable in the throttle state i,/>Indicating the minimum rotational speed that can be reached at throttle condition i. For example, when a higher throttle is used>When =5, the range of the rotational speed of the virtual fuel engine can be set to be within the range [ -j ]>，/>]Between them.

In this embodiment, when the previous non-shift state is determined that the shift state is the upshift based on the pedal depth and the running speed of the target vehicle, that is, when the current shift state is at the start of the upshift period, the predicted rotation speed of the entire upshift period may be predicted.

In a specific application scenario, for the first upshift phase T _fall The following formula may be employed:

wherein, Representing a linear interpolation operation, +.>The (first upshift coefficient) is an adjustable parameter, the naturalness of the converted sound corresponding to the upshift link is adjusted, and rpm data is stored in a queue form data structure. />For the maximum rotation speed value calculated for the corresponding throttle state quantity, namely the maximum rotation speed which can be achieved under the throttle state of the current time period, n represents the interpolation quantity, the first upshift stage can be divided into a plurality of time periods, each time period further comprises the same number of sampling points, and the rpm quantity contained in the interpolated data can be consistent with the number of the sampling points contained in the first upshift stage so as to represent the predicted rotation speed corresponding to each sampling point.

Step S633: and obtaining a first product of the maximum rotation speed and the first upshift coefficient, obtaining a second product of the maximum rotation speed and the second upshift coefficient, and interpolating between the first product and the second product to obtain the predicted rotation speed in the second upshift stage.

In a specific application scenario, for the second upshift phase T _attack The following formula may be employed:

wherein,representing a linear interpolation operation, +.>(first upshift coefficient) and +.>The (second upshift coefficient) is an adjustable parameter, the naturalness of the converted sound corresponding to the upshift link is adjusted, and rpm (rotating speed) data is stored in a queue form data structure. / >The second upshift stage can be divided into a plurality of time periods, each time period further comprises the same number of sampling points, and the rpm number contained in the interpolated data can be consistent with the number of the sampling points contained in the second upshift stage so as to represent the predicted rotating speed corresponding to each sampling point.

Step S634: and sequentially taking each time period in the third upshift stage as a first target time period, predicting the rotation speed of the last time period in the third upshift stage according to the rotation speed of the first target time period, and acquiring the predicted rotation speed of the first target time period based on the predicted rotation speed of the last time period.

Third upshift stage T _spike The method can be divided into a plurality of time periods, and the time periods are sequentially used as first target time periods according to the sequence.

In a specific application scenario, the driving speed may be mapped to the rotation speed by using a preset mapping manner for the first target periodThe calculation is performed at the rotation speed as the first target period. Or for the first target period, the rotation speed of the first target period can also be obtained based on interpolation operation corresponding to the previous period of the second target period 。

According to the rotational speed of the first target periodPredicting and updating rotational speed data +.f for the last period of time at the end of the entire upshift period using B-spline interpolation>. Then the rotation speed of the first sampling point in the last time period according to the prediction is +.>And the rotational speed of the tail sampling point +.>And the rotational speed of the first sampling point in the rotational speed of the first target period +.>B-spline interpolation calculation is also performed based on the data of the three points to obtain the predicted rotation speed of the first target time period>The original rotational speed +.A first target period is replaced>The output, the formula is as follows:

in the method, in the process of the invention,for the number of time periods remaining between the current time period and the last time period, L is the number of sampling points contained in one time period, +.>Representing the operation of computing the B-spline interpolation expression, +.>Representing B-spline interpolation operation based on interpolation expression while +.>And->An interpolation expression for predicting the rotational speed of the last time period and an interpolation expression for predicting the predicted rotational speed of the first target time period are represented, respectively.

In a specific application scenario, the third upshift stage includes 200 time periods, each time period is sequentially used as a first target time period, the rotation speed of the last time period of the third upshift stage, namely, the rotation speed of the 200 th time period is predicted by using the rotation speed of the current first target time period, and the predicted rotation speed of the current first target time period is obtained based on the predicted rotation speed of the last time period.

Of course, the above examples are only possible implementation manners in practical applications, and based on the foregoing implementation manners, the examples may be reasonably changed according to specific requirements of the practical applications, so as to adapt to the practical requirements. For example, the rotation speed beautifying mode in the switching period can be adjusted according to the actual application condition, and the rotation speed obtained by adopting a preset mapping mode can also be utilized for the actual running speed in the switching period, so that the smooth beautifying can be further carried out on the basis.

Referring to fig. 7, fig. 7 is a flowchart illustrating a further embodiment of step S130 of the present application. Specifically, step S130 may include:

step S731: and determining a downshift period with a length of a third preset duration according to the downshift switching state of the virtual engine.

The related description of step S731 may refer to the related content described previously with respect to step S531, and the related descriptions of step S732-step S733 may refer to the related content described previously with respect to step S532. The third preset time period is predetermined and can be adjusted according to the actual needs of the user. The downshift cycle includes a first downshift stage and a second downshift stage, which may be divided into a plurality of time periods, each time period being a unit duration.

In a specific application scenario, during a downshift, the engine speed is first increased steadily over a period of time (T _lift ) Then gradually and smoothly decrease over time to a corresponding rotational speed (T _land ). Correspondingly, the downshift cycle is:

wherein T is _downgear For the period of down shift, T _lift 、T _land A first downshift stage and a second downshift stage, respectively. The duration of the first and second downshift phases may also be predetermined and may be adjusted according to the actual situation.

Step S732: and obtaining the minimum rotation speed of the target vehicle in the currently determined accelerator state, obtaining a third product of the downshift coefficient and the maximum rotation speed of the target vehicle in the currently determined accelerator state, and interpolating between the minimum rotation speed and the third product to obtain the predicted rotation speed in the first downshift stage.

In this embodiment, when the previous non-shift state is determined that the shift state is a downshift based on the pedal depth and the running speed of the target vehicle, that is, when the current shift state is at the start of the downshift cycle, the predicted rotation speed of the entire downshift cycle may be predicted.

In one specific application scenario of the present invention,for the first downshift stage T _lift The following formula may be employed:

Wherein,representing a linear interpolation operation, +.>The (downshift coefficient) is an adjustable parameter corresponding to the adjustment of the naturalness of the downshift ring segment conversion sound, and rpm (rotating speed) data are stored in a queue form data structure. />Maximum rotational speed value calculated for the corresponding throttle state quantity, i.e. the maximum rotational speed that can be reached in the throttle state in the current time period,/->The minimum rotation speed value calculated for the corresponding throttle state quantity, namely the minimum rotation speed which can be achieved under the throttle state of the current time period, n represents the interpolation quantity, the first downshift stage can be divided into a plurality of time periods, each time period further comprises the same quantity of sampling points, and the rpm quantity contained in the interpolated data can be consistent with the quantity of the sampling points contained in the first downshift stage so as to represent the predicted rotation speed corresponding to each sampling point.

Step S733: and sequentially taking each time period in the second downshift stage as a second target time period, predicting the rotation speed of the last time period in the second downshift stage according to the rotation speed of the second target time period, and acquiring the predicted rotation speed of the second target time period based on the predicted rotation speed of the last time period.

Second downshift stage T _land The method can be divided into a plurality of time periods, and the time periods are sequentially used as second target time periods according to the sequence.

In a specific application scenario, the preset may be utilized for the second target time periodMapping the running speed to the rotating speed by a mapping modeThe rotation speed as the second target period is calculated. Or for the second target period, the rotation speed of the second target period may also be obtained based on interpolation operation corresponding to the previous period of the second target period。

The predicted rotational speed in the second downshift stage may be obtained in a similar manner to the third upshift stage, specifically in accordance with the rotational speed of the second target periodPredicting and updating rotational speed data +.f for the last period of time at the end of the entire upshift period using B-spline interpolation>. Then the rotation speed of the first sampling point in the last time period according to the prediction is +.>And the rotational speed of the tail sampling point +.>And the rotational speed of the first sampling point in the rotational speed of the second target period +.>B-spline interpolation calculation is likewise performed based on the data of the three points to obtain the predicted rotation speed +.>The original rotational speed +.>And outputting.

Referring to fig. 8, fig. 8 is a flowchart illustrating a further embodiment of step S130 of the present application. Specifically, step S130 may include:

step S831: and determining an accelerator switching period based on the accelerator switching period exit condition according to the switching state of the virtual engine as accelerator switching.

The related description of step S831 may refer to the related content described previously with respect to step S531, and the related description of step S832 may refer to the related content described previously with respect to step S532. The accelerator switching period is switched from an original accelerator state to a target accelerator state, one of the original accelerator state and the target accelerator state is a high accelerator state, and the other is a low accelerator state. The accelerator switch may be from a high accelerator state to a low accelerator state or from a low accelerator state to a high accelerator state.

In some embodiments, the original throttle state is the throttle state of the previous time period and the target throttle state is the throttle state of the current time period.

It can be appreciated that when the current time period determines that the switching state is accelerator switching, it can be determined that the accelerator state in the current time period is the target accelerator state of the accelerator switching period, and the accelerator state in the previous time period is the original accelerator state of the accelerator switching period.

The exit of the throttle switching period may include two types, one is that the throttle switching has been completed and the other is that the throttle switching is no longer performed. Specifically, when the accelerator is switched from the low accelerator state to the high accelerator state, the accelerator switching cycle exit condition may include: the speed of the current time period is greater than the speed corresponding to the target accelerator state, or the accelerator state of the current time period is less than the target accelerator state. Specifically, the expression can be represented as follows:

wherein,representing the speed of the current time period,/-, for example>For the target throttle state determined when entering the throttle switching cycle,/->Representing the corresponding speed of the target throttle state, which is obtained by parameter debugging in the research and development stage, namely corresponding to each throttle value of 0-5->。Indicating throttle status.

When the accelerator is switched from the high-accelerator state to the low-accelerator state, the accelerator switching cycle exit condition may include: the speed of the current time period is smaller than the speed corresponding to the target accelerator state, or the accelerator state of the current time period is larger than the target accelerator state. Specifically, the expression can be represented as follows:

in a specific application scenario, the entering of the accelerator switching period is judged in the current time period, in the subsequent time period, whether the time period is in the accelerator switching period or not can be determined according to the exiting condition of the accelerator switching period, and if the time period is in the accelerator switching period, the driving speed in the time period is mapped into the predicted rotating speed in a target mapping mode. If the time period meets the exit condition of the accelerator switching period, determining to exit the accelerator switching period from the time period, and additionally judging the switching state of the time period.

Step S832: and mapping the running speed in the accelerator switching period into the predicted rotating speed in the accelerator switching period by using a target mapping mode.

The target mapping mode is a mapping relation between the running speed and the rotating speed established based on the high-accelerator state and the low-accelerator state.

For the accelerator switching period, the predicted rotational speed in the accelerator switching period is optimized by reestablishing the rotational speed-speed mapping relationship between the low accelerator state and the high accelerator state, i.e., the target mapping manner, and by this specific target mapping manner.

In some embodiments, mapping the driving speed in the accelerator switching period to the predicted rotational speed in the accelerator switching period by using the target mapping manner may be implemented by: performing convex optimization processing on the difference between the running speed in the accelerator switching period and the speed in the low accelerator state to obtain a speed difference value after the convex optimization processing, obtaining a ratio of the difference between the preset rotating speed in the high accelerator state and the preset rotating speed in the low accelerator state to the difference between the speed in the high accelerator state and the speed in the low accelerator state, multiplying the ratio and the speed difference value after the convex optimization processing to obtain a fourth product, and adding the fourth product and the preset rotating speed in the low accelerator state to obtain the predicted rotating speed in the accelerator switching period.

In particular, the throttle switching phase may be divided into several time periods, each containing the same number of sampling points. The above-described operation is performed for the third target period of time for each period of time, respectively, and may be expressed specifically as follows:

wherein,representing a convex optimization operation, wherein->To correspond toAdjustable parameter of throttle switching state, +.>For the mean value of the driving speed in the third target period, +.>And->For the speed corresponding to the low throttle state when triggering the throttle switching cycle and the corresponding rotational speed +.>And->The speed and corresponding rotational speed for the high throttle condition at this time.

It will be appreciated that the high and low throttle states are fixed within the same throttle switching period, one being the original throttle state for that throttle switching period and the other being the target throttle state, as determined upon triggering the throttle switching period.The speed corresponding to the low throttle state can be the average running speed in the time period corresponding to the low throttle state, or the speed preset by the throttle state, +.>The corresponding rotating speed for the low throttle state can be +.>Mapping by using a preset mapping mode to obtain->The speed corresponding to the high accelerator state can be the average running speed in the time period corresponding to the high accelerator state, or the speed preset by the accelerator state, +. >The corresponding rotating speed for the high throttle state can be +.>And mapping by adopting a preset mapping mode.

In some embodiments, in a bench test (off-line simulation) scenario, the target vehicle is a test vehicle at bench test, and its travel speed may be obtained by real-time off-line vehicle speed simulation for the target vehicle. Specifically, acquiring the running speed of the target vehicle includes: and obtaining the pedal depth of the brake of the target vehicle, and predicting the running speed according to the pedal depth of the electric door and the brake of the target vehicle.

Further specifically, the simulation system of the virtual engine includes a real-time off-line vehicle speed simulation module for predicting a travel speed based on a pedal depth of a target vehicle electric door and a pedal depth of a target vehicle brake. The running speed can be obtained by a vehicle speed prediction model, and the vehicle speed prediction model integrally depends on parameters such as the weight of the whole vehicle, the running road condition of the vehicle, the power of the vehicle, the number of engine cylinders and the like.

In a specific application scenario, the parameterized and simplified formula is expressed as follows:

wherein, in the formula, the chemical formula,and->A real-time electric door pedal depth input sequence and a real-time brake pedal depth input sequence respectively>For the real-time simulation of the obtained offline vehicle speed sequence, +. >Between two discrete sample points which are discrete sequencesThe minimum time interval of (2) is the inverse of the discrete sequence frequency sampling rate, the corresponding differential equation can be realized by iterative solution, and further, the parameters of the differential equation are described as follows:

representing the total output power of the virtual engine, wherein the total output power is an adjustable parameter related to the power of the automobile and the number of engine cylinders; />Representing the conversion efficiency coefficient from the output thermal power to the mechanical power of the virtual fuel engine of the automobile; />Representing the wind resistance coefficient; />Representing the total weight of the whole vehicle; />Representing the comprehensive road condition resistance coefficient, including the friction coefficient of the running road surface, the gradient condition and the like; />Indicating the normalized brake transmission resistance coefficient.

According to the scheme, the switching state of the virtual engine is obtained based on the pedal depth and the running speed, the working state of the virtual engine of the target vehicle is further represented, further, the predicted rotating speed is determined based on the switching state of the virtual engine, the accuracy of engine simulation is improved, further, according to the characteristics of the switching process, the corresponding period is determined based on different switching states, the rotating speed in the switching period is predicted by adopting a scheme different from a preset mapping mode, and therefore the accuracy of virtual engine switching process simulation is improved, and the accuracy of virtual engine simulation is improved. Furthermore, for different switching periods, different prediction schemes are adopted, so that the virtual engine can be more accurately simulated according to the characteristics of each switching process.

After the predicted rotating speed of the target vehicle is obtained through the method, the predicted rotating speed can be used for synthesizing the sound waves of the virtual engine of the target vehicle, and particularly, the sound waves can be synthesized by adopting an order synthesis scheme, a wave table synthesis scheme and a particle synthesis scheme. The improvement of the simulation accuracy of the virtual engine can bring the improvement of the synthesis accuracy of the virtual engine sound waves, so that the accuracy and the authenticity of the sound wave audio of the virtual engine are improved, and a user can obtain more real sound wave experience of the engine of the fuel engine.

Referring to fig. 9, fig. 9 is a flowchart illustrating an engine simulation method according to another embodiment of the present application.

In this embodiment, the virtual engine equivalent predicted rotational speed is obtained by the simulation system of the virtual engine. The simulation system of the virtual engine includes a real-time state machine maintenance module. Fig. 9 shows a flow chart of signals in the real-time state machine maintenance module. Wherein,representing the pedal depth of the electric gate averaged over a period of time, calculated as a percentage,// represents the rounding after division. />Representing the average speed of travel over a period of time,&&representing a logical and.

The throttle state is determined based on the pedal depth sequence seqPedal of the electric valve, and the throttle state shift 0- >5 corresponds to the pedal depth of the electric valve of 0% -100%, wherein the pedal depth sequence seqPedal of the electric valve and the real-time acquired running speed sequence seqSpeed are taken as inputs. The state of motion state motion is determined based on the pedal depth sequence seqpeer and the travel speed sequence seqSpeed of the electric valve together. Then, the switching state stateShift is determined according to the throttle state stateThrottle and the motion state stateMotion. When the motion state=2, the switching state is not switching, characterized by a value of 0; when the motion state=0, the switching state is not switching, characterized by a value of 0; when the motion state=1, there are four scenes, the switching state is not switching, and the value is represented by 0; the switching state is upshift switching, which is represented by a value 1, the switching state is downshift switching, which is represented by a value 2; the switching state is throttle switching and is represented by a value of 3.

The seq indicates that the data corresponding to one time period is sequence data, including the data of each sampling point in the time period, and the state indicates the value corresponding to one time period, so that the calculation amount of the whole scheme can be reduced. For example, the pedal depth of the electric door for the current time period includes the pedal depths of L sampling points, and the throttle state for the current time period is determined to be 0 based on the L pedal depths.

Referring to fig. 10, fig. 10 is a schematic flow chart of an embodiment of a method for synthesizing acoustic waves according to the present application. Specifically, the method may comprise the steps of:

step S1010: based on the pedal depth and the running speed of the electric door of the target vehicle, the switching state and the predicted rotational speed of the virtual engine of the target vehicle are obtained.

The switching state and the predicted rotation speed of the virtual engine may be obtained by using any virtual engine simulation method in the foregoing embodiments, and the specific description may refer to the content in the foregoing embodiments, which is not described herein.

Step S1020: and synthesizing to obtain the sound wave data of the target vehicle based on the switching state and the predicted rotating speed.

The method for synthesizing the sound waves may include, but is not limited to, an order synthesis scheme, a wave table synthesis scheme, and a particle synthesis scheme, and the following description will take the virtual engine sound waves of the target vehicle synthesized by the particle synthesis scheme as an example.

In a specific application scenario, the synthesis of the acoustic waves can be realized by the following steps: the method comprises the steps of obtaining an audio particle set of a virtual engine of a target vehicle in different switching states, obtaining running information of the target vehicle, obtaining the switching state and the predicted rotating speed of the virtual engine of the target vehicle based on the running information, selecting matched audio particles from the audio particle set to serve as target audio particles based on the switching state and the predicted rotating speed, and synthesizing sound wave data of the target vehicle based on the target audio particles which are cached currently.

Wherein the set of audio particles of the virtual engine in different switching states is predetermined. The audio particle set comprises audio particles corresponding to each rotating speed respectively, and the driving information comprises the pedal depth and the driving speed of the electric door. Specifically, a corresponding set of audio particles is selected based on the switching state, and matching audio particles are selected as target audio particles from the set of audio particles that have been selected according to the predicted rotation speed.

According to the scheme, the improvement of the simulation accuracy of the virtual engine can bring the improvement of the accuracy of the synthesis of the virtual engine sound waves, so that the accuracy and the authenticity of the sound wave audio of the virtual engine are improved, and a user can obtain more real sound wave experience of the engine of the fuel engine.

Referring to fig. 11, fig. 11 is a schematic flow chart of another embodiment of the method for synthesizing acoustic waves according to the present application.

The engine simulation method can be suitable for real vehicle operation and bench test scenes, and the application scenes are wide. In this embodiment, an example of an actual vehicle operation scenario will be described. The virtual engine equivalent predicted rotating speed is obtained by a virtual engine simulation system, and the virtual engine simulation system comprises a real-time state machine maintenance module, wherein the real-time state machine maintenance module comprises a motion state machine, an accelerator state machine, a switching state machine and a gear state machine. The real-time electric door pedal depth and the real-time running speed are input into a simulation system of the virtual engine to obtain a motion state, an accelerator state, a switching state and a gear state, and the virtual engine equivalent predicted rotating speed is obtained based on the switching state. Based on basic working state output (acceleration, deceleration or idling) of the virtual fuel engine and corresponding real-time virtual fuel engine rotating speed sequence output, the sound synthesis of active sound waves in the vehicle can be further realized by adopting modes such as particle synthesis and the like to obtain sound wave audio of the simulated engine. Further, the real-time virtual fuel engine rotational speed sequence output based on the basic working state output (acceleration, deceleration or idling) of the virtual fuel engine and corresponding gear segmentation synthesizes the simulated engine sound wave audio.

Referring to fig. 12, fig. 12 is a schematic flow chart of a method for synthesizing acoustic waves according to another embodiment of the present application.

In this embodiment, a bench test or an off-line simulation scenario is taken as an example for explanation. The equivalent predicted rotating speed of the virtual engine is obtained by a simulation system of the virtual engine, and the simulation system of the virtual engine comprises a real-time state machine maintenance module and a real-time offline vehicle speed simulation module. The real-time electric door pedal depth and the real-time brake pedal depth are used as the input of a real-time offline vehicle speed simulation module, and the real-time simulation vehicle speed is predicted by utilizing a vehicle speed prediction model and combining parameters such as the weight of the whole vehicle, the running road condition of the vehicle, the power of the vehicle, the number of engine cylinders and the like. The vehicle driving road condition is a simulated road condition. And inputting the real-time electric door pedal depth and the real-time simulated vehicle speed into a real-time state machine maintenance module to obtain a motion state, an accelerator state, a switching state and a gear state, and obtaining the equivalent predicted rotating speed of the virtual engine based on the switching state. Based on basic working state output (acceleration, deceleration or idling) of the virtual fuel engine and corresponding real-time virtual fuel engine rotating speed sequence output, the sound synthesis of active sound waves in the vehicle can be further realized by adopting modes such as particle synthesis and the like to obtain sound wave audio of the simulated engine. Further, the real-time virtual fuel engine rotational speed sequence output based on the basic working state output (acceleration, deceleration or idling) of the virtual fuel engine and corresponding gear segmentation synthesizes the simulated engine sound wave audio.

Referring to fig. 13, fig. 13 is a schematic diagram of a framework of an embodiment of an engine simulation device of the present application.

In this embodiment, the engine simulation device 130 includes an acquisition module 131, a determination module 132, and a prediction module 133, where the acquisition module 131 is configured to acquire a pedal depth of a target vehicle electric door, and acquire a running speed of the target vehicle; the determining module 132 is configured to determine a switching state of a virtual engine of the target vehicle based on the pedal depth and the travel speed; wherein the switching state is any one of non-switching, upshift switching, downshift switching and accelerator switching; the prediction module 133 is configured to obtain a predicted rotational speed equivalent to the virtual engine at the pedal depth and the running speed based on the switching state of the virtual engine.

Wherein the determining module 132 includes a first determining submodule and a second determining submodule, the first determining submodule is used for determining a motion state of the target vehicle based on the pedal depth and the running speed and determining a throttle state of the virtual engine based on the pedal depth; the second determination submodule is used for determining the switching state of the virtual engine based on the motion state and the accelerator state.

The second determining submodule comprises at least one of a first response unit and a second response unit, wherein the first response unit is used for determining that the switching state of the target vehicle is not switching in response to the motion state being deceleration or idling; the second response unit is used for responding to the motion state as acceleration and determining the switching state of the virtual engine based on the throttle state.

The second response unit comprises an acquisition subunit and a determination subunit, wherein the acquisition subunit is used for acquiring a first judgment result of the current cycle type of the virtual engine based on the switching state determined before the virtual engine; the first judging result represents whether the virtual engine is in any cycle type of an upshift cycle, a downshift cycle and an accelerator switching cycle at present; the determining subunit is used for determining the current switching state of the virtual engine based on the first judging result and the throttle state.

The determining subunit is configured to determine, based on the first determination result and the accelerator state, a current switching state of the virtual engine when the first determination result indicates that the virtual engine is not currently in any cycle type of an upshift cycle, a downshift cycle, and an accelerator switching cycle, where the determining subunit specifically includes: obtaining a detection result representing whether the state of the accelerator changes; based on the detection result, selecting any one of a second judgment result and a previous pedal depth, and determining the current switching state of the virtual engine; and the second judgment result represents whether the upshift condition and the downshift condition are met.

The determining subunit is configured to select any one of the second determination result and the previous pedal depth based on the detection result, and determine a current switching state of the virtual engine, and specifically includes at least one of the following: responding to the detection result to represent that the throttle state is unchanged, and determining the current switching state of the virtual engine based on a second judgment result; and responding to the detection result to represent the change of the state of the accelerator, and determining the current switching state of the virtual engine based on the previous pedal depth.

The first determination submodule comprises an acquisition unit and a selection unit, wherein the acquisition unit is used for acquiring an average value of pedal depth in a first preset time period before; the selection unit is used for selecting one of a plurality of preset throttle states as the throttle state based on the average value of the pedal depth.

The prediction module 133 includes a third determination submodule and a prediction submodule, where the third determination submodule is configured to determine a corresponding period based on a switching state of the virtual engine; the prediction submodule is used for obtaining the predicted rotating speed of the virtual engine in the period corresponding to the switching state based on the throttle state of the virtual engine; the throttle state is determined based on the pedal depth of the electric valve, and represents the equivalent opening and closing fuel injection quantity of the virtual engine corresponding to the pedal depth of the electric valve.

The third determining submodule is used for determining a corresponding period based on the switching state of the virtual engine, and specifically comprises the following steps: according to the switching state of the virtual engine, the upshift switching is carried out, an upshift period with the length of a second preset duration is determined, the upshift period comprises a first upshift stage, a second upshift stage and a third upshift stage, and the third upshift stage is divided into a plurality of time periods; the prediction submodule is used for obtaining the predicted rotating speed of the virtual engine in the period corresponding to the switching state based on the throttle state of the virtual engine, and specifically comprises the following steps: obtaining the maximum rotating speed of the target vehicle in the currently determined accelerator state, obtaining a first product of the maximum rotating speed and a first upshift coefficient, and interpolating between the maximum rotating speed and the first product to obtain the predicted rotating speed in a first upshift stage; obtaining a first product of the maximum rotation speed and a first upshift coefficient, obtaining a second product of the maximum rotation speed and a second upshift coefficient, and interpolating between the first product and the second product to obtain a predicted rotation speed in a second upshift stage; and sequentially taking each time period in the third upshift stage as a first target time period, predicting the rotation speed of the last time period in the third upshift stage according to the rotation speed of the first target time period, and acquiring the predicted rotation speed of the first target time period based on the predicted rotation speed of the last time period.

The third determining submodule is configured to determine, based on the switching state of the virtual engine, a corresponding period specifically includes: determining a downshift period with a third preset duration according to the shift state of the virtual engine as downshift shift, wherein the downshift period comprises a first downshift stage and a second downshift stage, and the second downshift stage is divided into a plurality of time periods; the prediction submodule is used for obtaining the predicted rotating speed of the virtual engine in the period corresponding to the switching state based on the throttle state of the virtual engine, and specifically comprises the following steps: obtaining the minimum rotation speed of the target vehicle in the currently determined throttle state, obtaining a third product of the downshift coefficient and the maximum rotation speed of the target vehicle in the currently determined throttle state, and interpolating between the minimum rotation speed and the third product to obtain the predicted rotation speed in the first downshift stage; and sequentially taking each time period in the second downshift stage as a second target time period, predicting the rotation speed of the last time period in the second downshift stage according to the rotation speed of the second target time period, and acquiring the predicted rotation speed of the second target time period based on the predicted rotation speed of the last time period.

The third determining submodule is used for determining a corresponding period based on the switching state of the virtual engine, and specifically comprises the following steps: determining an accelerator switching period based on an exit condition of the accelerator switching period according to the switching state of the virtual engine as accelerator switching, wherein the accelerator switching period represents switching from an original accelerator state to a target accelerator state, one of the original accelerator state and the target accelerator state is a high accelerator state, and the other is a low accelerator state; the prediction submodule is used for obtaining the predicted rotating speed of the virtual engine in the period corresponding to the switching state based on the throttle state of the virtual engine, and specifically comprises the following steps: and mapping the running speed in the accelerator switching period into the predicted rotating speed in the accelerator switching period by using a target mapping mode, wherein the target mapping mode is a mapping relation between the running speed and the rotating speed established based on the high accelerator state and the low accelerator state.

The prediction sub-module is configured to map a running speed in an accelerator switching period to a predicted rotation speed in the accelerator switching period by using a target mapping manner, and specifically includes: performing convex optimization processing on the difference between the running speed in the accelerator switching period and the speed in the low accelerator state to obtain a speed difference value after the convex optimization processing, obtaining a ratio of the difference between the preset rotating speed in the high accelerator state and the preset rotating speed in the low accelerator state to the difference between the speed in the high accelerator state and the speed in the low accelerator state, multiplying the ratio and the speed difference value after the convex optimization processing to obtain a fourth product, and adding the fourth product and the preset rotating speed in the low accelerator state to obtain the predicted rotating speed in the accelerator switching period.

The acquiring module 131 includes an acquiring sub-module and a speed predicting sub-module, where the acquiring sub-module is used to acquire a pedal depth of a brake of the target vehicle; the speed prediction submodule is used for predicting the running speed according to the pedal depth of the electric door and the brake of the target vehicle.

Referring to fig. 14, fig. 14 is a schematic diagram of a frame of an embodiment of a wave synthesizing apparatus according to the present application.

In this embodiment, the sound wave synthesizing apparatus 140 includes a prediction module 141 and a synthesizing module 142, where the prediction module 141 is configured to obtain a switching state and a predicted rotational speed of a virtual engine of a target vehicle based on a pedal depth and a running speed of an electric door of the target vehicle; the switching state and the predicted rotating speed are obtained based on the engine simulation device; the synthesizing module 142 is configured to synthesize sound wave data of the target vehicle based on the switching state and the predicted rotational speed.

Referring to fig. 15, fig. 15 is a schematic frame diagram of an embodiment of an electronic device of the present application.

In this embodiment, the electronic device 150 includes a memory 151 and a processor 152, wherein the memory 151 is coupled to the processor 152. In particular, various components of the electronic device 150 may be coupled together by a bus, or the processor 152 of the electronic device 150 may be coupled to each other individually. The electronic device 150 may be any device having processing capabilities, such as a computer, tablet, cell phone, etc.

The memory 151 is used for storing program data executed by the processor 152, data during processing by the processor 152, and the like. Such as travel speed, pedal depth, audio particles, etc. Wherein the memory 151 includes a nonvolatile storage portion for storing the above-described program data.

The processor 152 controls the operation of the electronic device 150, the processor 152 may also be referred to as a CPU (Central Processing Unit ). The processor 152 may be an integrated circuit chip having signal processing capabilities. The processor 152 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. In addition, the processor 152 may be commonly implemented by a plurality of circuit-forming chips.

The processor 152 executes instructions to implement any of the engine simulation methods or the acoustic wave synthesizing methods described above by calling program data stored in the memory 151.

Referring to fig. 16, fig. 16 is a schematic diagram illustrating an embodiment of a computer readable storage medium according to the present application.

In this embodiment, the computer readable storage medium 160 stores program data 161 executable by a processor, and the program data 161 can be executed to implement any of the engine simulation method or the wave synthesis method.

The computer readable storage medium 160 may be a medium such as a usb (universal serial bus), a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, which may store program data, or may be a server storing the program data 161, and the server may send the stored program data to another device for execution, or may also self-execute the stored program data.

In some embodiments, computer-readable storage medium 160 may also be a memory as shown in FIG. 15.

Referring to fig. 17, fig. 17 is a schematic diagram of a frame of an embodiment of a vehicle of the present application.

In this embodiment, the vehicle 170 includes a vehicle body 171 and an intelligent device 172 carried on the vehicle body, where the intelligent device may be an electronic device shown in fig. 15, and any of the engine simulation method or the acoustic wave synthesizing method described above may be implemented. The relevant descriptions may refer to the relevant content of the foregoing embodiments, and are not described herein.

The foregoing description is only of embodiments of the present application, and is not intended to limit the scope of the patent application, and all equivalent structures or equivalent processes using the descriptions and the contents of the present application or other related technical fields are included in the scope of the patent application.

Claims

1. An engine simulation method, the method comprising:

acquiring the pedal depth of a target vehicle electric door and acquiring the running speed of the target vehicle;

determining a motion state of the target vehicle based on the pedal depth and the travel speed, and determining a throttle state of a virtual engine based on the pedal depth; determining a switching state of the virtual engine based on the motion state and the throttle state; wherein the motion state is any one of acceleration, deceleration and idle speed, and the switching state is any one of non-switching, upshift switching, downshift switching and accelerator switching;

Determining a corresponding period based on the switching state of the virtual engine;

based on the throttle state of the virtual engine, obtaining the predicted rotating speed of the virtual engine in the period corresponding to the switching state; the accelerator state is determined based on the pedal depth of the electric valve, and represents the equivalent opening and closing fuel injection quantity of the virtual engine corresponding to the pedal depth of the electric valve, and the predicted rotating speed represents the equivalent rotating speed of the virtual engine under the pedal depth and the running speed;

wherein the determining the switching state of the virtual engine based on the motion state and the throttle state includes at least one of:

determining a switching state of the target vehicle as the non-switching in response to the motion state being the deceleration or the idle speed;

and determining a switching state of the virtual engine based on the throttle state in response to the motion state being the acceleration.

2. The method of claim 1, wherein the determining the switching state of the virtual engine based on the throttle state comprises:

based on the switching state determined before the virtual engine, acquiring a first judgment result of the current cycle type of the virtual engine; the first judging result represents whether the virtual engine is in any cycle type of an upshift cycle, a downshift cycle and an accelerator switching cycle at present;

And determining the current switching state of the virtual engine based on the first judging result and the throttle state.

3. The method according to claim 2, wherein, in a case where the first determination result indicates that the virtual engine is not currently in any of the cycle types of the upshift cycle, the downshift cycle, and the throttle switching cycle, the determining the current switching state of the virtual engine based on the first determination result and the throttle state includes:

obtaining a detection result representing whether the throttle state changes;

based on the detection result, selecting any one of a second judgment result and a previous pedal depth, and determining the current switching state of the virtual engine; and the second judgment result represents whether an upshift condition and a downshift condition are met.

4. The method of claim 1, wherein the determining the corresponding period based on the switching state of the virtual engine comprises:

determining an upshift period with a second preset duration according to the upshift switching state of the virtual engine, wherein the upshift period comprises a first upshift stage, a second upshift stage and a third upshift stage, and the third upshift stage is divided into a plurality of time periods;

The obtaining, based on the throttle state of the virtual engine, the predicted rotation speed of the virtual engine in the period corresponding to the switching state includes:

obtaining the maximum rotating speed of the target vehicle in the currently determined accelerator state, obtaining a first product of the maximum rotating speed and a first upshift coefficient, and interpolating between the maximum rotating speed and the first product to obtain the predicted rotating speed in the first upshift stage;

obtaining a first product of the maximum rotation speed and a first upshift coefficient, obtaining a second product of the maximum rotation speed and a second upshift coefficient, and interpolating between the first product and the second product to obtain a predicted rotation speed in the second upshift stage;

and sequentially taking each time period in the third upshift stage as a first target time period, predicting the rotating speed of the last time period in the third upshift stage according to the rotating speed of the first target time period, and acquiring the predicted rotating speed of the first target time period based on the predicted rotating speed of the last time period.

5. The method of claim 1, wherein the determining the corresponding period based on the switching state of the virtual engine comprises:

Determining a downshift period with a third preset duration according to the downshift switching state of the virtual engine, wherein the downshift period comprises a first downshift stage and a second downshift stage, and the second downshift stage is divided into a plurality of time periods;

obtaining the minimum rotation speed of the target vehicle in the currently determined throttle state, obtaining a third product of a downshift coefficient and the maximum rotation speed of the target vehicle in the currently determined throttle state, and interpolating between the minimum rotation speed and the third product to obtain the predicted rotation speed in the first downshift stage;

and sequentially taking each time period in the second downshift stage as a second target time period, predicting the rotating speed of the last time period in the second downshift stage according to the rotating speed of the second target time period, and acquiring the predicted rotating speed of the second target time period based on the predicted rotating speed of the last time period.

6. The method of claim 1, wherein the determining the corresponding period based on the switching state of the virtual engine comprises:

Determining an accelerator switching period based on an accelerator switching period exit condition according to the switching state of the virtual engine as the accelerator switching, wherein the accelerator switching period represents switching from an original accelerator state to a target accelerator state, one of the original accelerator state and the target accelerator state is a high accelerator state, and the other is a low accelerator state;

and mapping the running speed in the accelerator switching period into a predicted rotating speed in the accelerator switching period by using a target mapping mode, wherein the target mapping mode is a mapping relation between the running speed and the rotating speed, which is established based on the high accelerator state and the low accelerator state.

7. The method of claim 6, wherein mapping the travel speed within the throttle switching period to a predicted rotational speed within the throttle switching period using a target map comprises:

and performing convex optimization processing on the difference between the running speed in the accelerator switching period and the speed in the low accelerator state to obtain a speed difference value after the convex optimization processing, obtaining a ratio of the difference between the preset rotating speed in the high accelerator state and the preset rotating speed in the low accelerator state to the difference between the speed in the high accelerator state and the speed in the low accelerator state, multiplying the ratio and the speed difference value after the convex optimization processing to obtain a fourth product, and adding the fourth product and the preset rotating speed in the low accelerator state to obtain the predicted rotating speed in the accelerator switching period.

8. A method of synthesizing a sound wave, comprising:

obtaining a switching state and a predicted rotating speed of a virtual engine of a target vehicle based on a pedal depth and a running speed of an electric door of the target vehicle; wherein the switching state and the predicted rotational speed are obtained based on the engine simulation method of any one of claims 1 to 7;

and synthesizing to obtain the sound wave data of the target vehicle based on the switching state and the predicted rotating speed.

9. An electronic device comprising a memory and a processor coupled to each other, the processor configured to execute program data stored in the memory to implement the engine simulation method of any one of claims 1 to 7 or the acoustic wave synthesis method of claim 8.

10. A vehicle, characterized in that the vehicle comprises:

a vehicle body;

an intelligent device carried on the vehicle body, and the intelligent device is the electronic device of claim 9.

11. A computer readable storage medium having stored thereon program data, wherein the program data, when executed by a processor, implements the engine simulation method of any one of claims 1 to 7 or the acoustic wave synthesizing method of claim 8.