CN117944459A

CN117944459A - Method, device, equipment and storage medium for electrically driven system parameters

Info

Publication number: CN117944459A
Application number: CN202410197258.9A
Authority: CN
Inventors: 赵佳伟; 张扬; 卢国成; 栾文悦; 李夏
Original assignee: Deep Blue Automotive Technology Co ltd
Current assignee: Deep Blue Automotive Technology Co ltd
Priority date: 2024-02-22
Filing date: 2024-02-22
Publication date: 2024-04-30
Anticipated expiration: 2044-02-22
Also published as: CN117944459B

Abstract

The application relates to an electric drive system parameter method, an electric drive system parameter device, electric drive system parameter equipment and a storage medium, and relates to the technical field of vehicles. The method comprises the following steps: determining working condition clustering center points of multiple groups of electric drive system loss models; aiming at each group of electric drive system loss models, obtaining the efficiency of working condition clustering center points of the electric drive system loss models; the efficiency of the driving working condition center point is driving efficiency, and the efficiency of the recovery working condition center point is recovery efficiency; based on the driving efficiency and the recovery efficiency, determining the comprehensive efficiency of the loss model of the electric drive system so as to obtain the comprehensive efficiency of each group of loss models of the electric drive system in a plurality of groups of electric drive loss model combinations; determining target system parameters according to the comprehensive efficiency of each group of electric drive system loss models in the multiple groups of electric drive loss model combinations; the target system parameter is used to adjust an electric drive system of the vehicle. Therefore, the system parameters of the electric drive system can be effectively determined, and the electric drive system can be adjusted based on the system parameters.

Description

Method, device, equipment and storage medium for electrically driven system parameters

Technical Field

The application relates to the technical field of vehicles, in particular to a method, a device, equipment and a storage medium for parameters of an electric drive system.

Background

Currently, the requirements of users on the driving range of electric vehicles are gradually increased, and besides the mode of increasing the battery capacity, another main method is to reduce the energy consumption of the electric vehicles. Among them, the electric drive system of the electric automobile is used as a core component, and the high-efficiency electric drive system is the focus of attention of vehicle manufacturers.

Under normal conditions, the traditional electric drive system parameters need to consider the influences of the whole vehicle running condition, the efficiency map of the motor system, the speed ratio of the speed reducer and the like, and the equipment can calculate and determine the comprehensive efficiency of each electric drive system so as to evaluate and analyze the electric drive system, but the problems that the electric drive system parameters are long in matching design period and are not optimal are solved.

Disclosure of Invention

The application provides a method, a device, equipment and a storage medium for electrically driving system parameters, which can effectively determine the system parameters of an electrically driving system and adjust the electrically driving system based on the system parameters. The technical scheme of the application is as follows:

According to a first aspect of the present application, there is provided a method for determining parameters of an electric drive system, applied to a vehicle, comprising: determining working condition clustering center points of multiple groups of electric drive system loss models; the system parameters in any two groups of electric drive system loss models are different, and the working condition clustering center points comprise a driving working condition center point and a recovery working condition center point; the working condition clustering center point is a center point determined by the working condition of the electric drive assembly through a clustering algorithm; aiming at each group of electric drive system loss models, obtaining the efficiency of working condition clustering center points of the electric drive system loss models; the efficiency of the driving working condition center point is driving efficiency, and the efficiency of the recovery working condition center point is recovery efficiency; based on the driving efficiency and the recovery efficiency, determining the comprehensive efficiency of the loss model of the electric drive system so as to obtain the comprehensive efficiency of each group of loss models of the electric drive system in a plurality of groups of electric drive loss model combinations; determining target system parameters according to the comprehensive efficiency of each group of electric drive system loss models in the multiple groups of electric drive loss model combinations; the target system parameters are system parameters corresponding to a target electric drive loss model with the greatest comprehensive efficiency in the combination of the plurality of groups of electric drive loss models; the target system parameter is used to adjust an electric drive system of the vehicle.

According to the technical means, the efficiency of the working condition clustering center point of the electric drive system loss model can be obtained for each group of electric drive system loss models, the comprehensive efficiency of the electric drive system loss models is determined through the efficiency, and because the electric control loss models, the motor loss models and the speed reducer loss models in each group of electric drive loss model combinations are different, the system parameters provided by the electric control loss models, the motor loss models and the speed reducer loss models are different, and further the comprehensive efficiency determined through calculation of each group of electric drive loss model combinations is different, so that the accuracy of the comprehensive efficiency determined by each group of electric drive loss model combinations is ensured.

In one possible implementation manner, for each group of electric drive system loss models, obtaining efficiency of working condition clustering center points of the electric drive system loss models includes: acquiring electric control current and system parameters of a working condition clustering center point of an electric drive system loss model; the electric control current is determined according to the working condition of the motor; the motor working conditions comprise a rotating speed working condition and a torque working condition; determining electric drive loss power corresponding to a working condition clustering center point based on electric control current, system parameters and motor working conditions; the system parameters comprise electric control loss parameters corresponding to the electric control loss model, motor loss parameters corresponding to the motor loss model and reducer loss parameters corresponding to the reducer loss model; and determining the efficiency of the working condition clustering center point of the electric drive system loss model based on the electric drive loss power.

According to the technical means, the efficiency of the working condition clustering center point of the electric drive system loss model can be determined, guidance is provided for development and design of the electric drive system, the electric drive system parameters are quickly matched and optimized to be designed with the electric drive efficient design as a target, and the electric drive development period is shortened.

In one possible implementation manner, determining the electric drive loss power corresponding to the working condition clustering center point based on the electric control current, the system parameters and the working condition of the motor comprises: determining electric control loss power, motor loss power and reducer loss power of a working condition clustering center point based on electric control current, system parameters and motor working conditions; and taking the sum of the electric control loss power, the motor loss power and the reducer loss power as the electric drive loss power.

According to the technical means, when the electric drive loss power is determined, different system parameters, electric control current and motor working conditions are fully considered, the loss power of the parts in the electric drive system of the working condition clustering center point is determined, and the electric drive loss power is effectively determined through the loss power of the parts, so that the accuracy of the subsequent determination of the comprehensive efficiency is ensured.

In one possible embodiment, the electric drive loss power comprises an electric drive loss power driving a center point of the operating condition; based on the electric drive loss power, determining the efficiency of the working condition clustering center point of the electric drive system loss model comprises the following steps: determining driving input energy and driving output energy according to the electric driving loss power of the driving working condition center point; and taking the ratio of the driving input energy to the driving output energy as the driving efficiency of the driving working condition center point.

In one possible embodiment, the electric drive loss power further comprises recovering the electric drive loss power of the operating center point; the method further comprises the steps of: according to the electric drive loss power of the center point of the recovery working condition, the recovery input energy and the recovery output energy are determined; and taking the ratio of the recovered input energy to the recovered output energy as the recovery efficiency of the recovery working condition center point.

According to the technical means, the driving efficiency of the driving working condition center point and the recovery efficiency of the recovery working condition center point under different conditions can be determined by considering the electric drive loss power of the driving working condition center point and the electric drive loss power of the recovery working condition center point, various conditions are fully considered, a series of parameters which are determined later are accurate, and the target system parameters are ensured to be more reliable.

In one possible implementation manner, obtaining an electric control current corresponding to an electric drive system loss model includes: determining a gear tooth array of the speed reducer based on a speed reducer model in the electric drive system loss model; under the condition that the gear tooth array meets the preset condition, determining the motor working condition corresponding to the electric drive system loss model based on the gear tooth array; the preset condition is that the number of teeth of each gear in the gear tooth array is larger than a threshold value, and the transmission ratio of a secondary gear in the gear tooth array is larger than that of a primary gear; and determining the electric control current corresponding to the loss model of the electric drive system according to the working condition of the motor.

In one possible embodiment, the method further comprises: and updating the number of teeth in the gear tooth array under the condition that the gear tooth array does not meet the preset condition.

According to the technical means, whether the gear tooth array provided by the speed reducer model is reasonable or not can be judged, under the reasonable condition, the gear transmission precision is high, the corresponding gear transmission stability is good, the transmission ratio (speed ratio) and the motor working condition can be calculated, and the electric control current corresponding to the electric drive system loss model is determined; in the case of an unreasonable gear tooth array, problems of poor bearing capacity of the gear and severe shock and vibration may occur, so that the number of teeth in the updated gear tooth array may be modified.

According to a second aspect of the present application, there is provided an electric drive system parameter determining apparatus, for use in a vehicle, the apparatus comprising: a processing unit and an acquisition unit; the processing unit is used for determining working condition clustering center points of the multiple groups of electric drive system loss models; the system parameters in any two groups of electric drive system loss models are different, and the working condition clustering center points comprise a driving working condition center point and a recovery working condition center point; the working condition clustering center point is a center point determined by the working condition of the electric drive assembly through a clustering algorithm; the acquisition unit is used for acquiring the efficiency of the working condition clustering center point of the electric drive system loss model aiming at each group of electric drive system loss models; the efficiency of the driving working condition center point is driving efficiency, and the efficiency of the recovery working condition center point is recovery efficiency; the processing unit is also used for determining the comprehensive efficiency of the electric drive system loss model based on the driving efficiency and the recovery efficiency so as to obtain the comprehensive efficiency of each group of electric drive system loss models in the combination of multiple groups of electric drive loss models; the processing unit is also used for determining target system parameters according to the comprehensive efficiency of each group of electric drive system loss models in the multiple groups of electric drive loss model combinations; the target system parameters are system parameters corresponding to a target electric drive loss model with the greatest comprehensive efficiency in the combination of the plurality of groups of electric drive loss models; the target system parameter is used to adjust an electric drive system of the vehicle.

In a possible implementation manner, the obtaining unit is further configured to obtain an electric control current and a system parameter of a working condition cluster center point of the loss model of the electric drive system; the electric control current is determined according to the working condition of the motor; the motor working conditions comprise a rotating speed working condition and a torque working condition; the processing unit is also used for determining the electric drive loss power corresponding to the working condition clustering center point based on the electric control current, the system parameters and the working condition of the motor; the system parameters comprise electric control loss parameters corresponding to the electric control loss model, motor loss parameters corresponding to the motor loss model and reducer loss parameters corresponding to the reducer loss model; and the processing unit is also used for determining the efficiency of the working condition clustering center point of the electric drive system loss model based on the electric drive loss power.

In a possible implementation manner, the processing unit is specifically configured to: determining electric control loss power, motor loss power and reducer loss power of a working condition clustering center point based on electric control current, system parameters and motor working conditions; and taking the sum of the electric control loss power, the motor loss power and the reducer loss power as the electric drive loss power.

In one possible embodiment, the electric drive loss power comprises an electric drive loss power driving a center point of the operating condition; the processing unit is specifically used for: determining driving input energy and driving output energy according to the electric driving loss power of the driving working condition center point; and taking the ratio of the driving input energy to the driving output energy as the driving efficiency of the driving working condition center point.

In one possible embodiment, the electric drive loss power further comprises recovering the electric drive loss power of the operating center point; the processing unit is specifically used for: according to the electric drive loss power of the center point of the recovery working condition, the recovery input energy and the recovery output energy are determined; and taking the ratio of the recovered input energy to the recovered output energy as the recovery efficiency of the recovery working condition center point.

In a possible embodiment, the processing unit is further configured to: determining a gear tooth array of the speed reducer based on a speed reducer model in the electric drive system loss model; under the condition that the gear tooth array meets the preset condition, determining the motor working condition corresponding to the electric drive system loss model based on the gear tooth array; the preset condition is that the number of teeth of each gear in the gear tooth array is larger than a threshold value, and the transmission ratio of a secondary gear in the gear tooth array is larger than that of a primary gear; and determining the electric control current corresponding to the loss model of the electric drive system according to the working condition of the motor.

In a possible embodiment, the processing unit is further configured to: and updating the number of teeth in the gear tooth array under the condition that the gear tooth array does not meet the preset condition.

According to a third aspect of the present application, there is provided an electronic apparatus comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement the method of the first aspect and any of its possible embodiments described above.

According to a fourth aspect of the present application there is provided a computer readable storage medium, which when executed by a processor of an electronic device, enables the electronic device to perform the method of the first aspect and any of its possible embodiments.

According to a fifth aspect of the present application there is provided a computer program product comprising computer instructions which, when run on an electronic device, cause the electronic device to perform the method of the first aspect and any of its possible embodiments.

Therefore, the technical characteristics of the application have the following beneficial effects:

(1) The system parameter determining device not only can acquire the efficiency of the working condition clustering center point of the electric drive system loss model aiming at each group of electric drive system loss models, and can determine the comprehensive efficiency of the electric drive system loss models according to the efficiency, but also can determine the target electric drive loss model according to the comprehensive efficiency of each group of electric drive system loss models in a plurality of groups of electric drive loss model combinations, and further can adjust the electric drive system of the vehicle according to the target system parameters by taking the system parameters corresponding to the target electric drive loss models as the target system parameters and adjusting the electric drive system of the vehicle according to the target system parameters so as to support the acceptance of the high efficiency index of the electric drive system.

(2) The efficiency of the working condition clustering center point of the electric drive system loss model can be determined, guidance is provided for development and design of the electric drive system, the aim of electric drive efficient design is achieved, quick matching and optimizing design is conducted on electric drive system parameters, and the electric drive development period is shortened.

(3) When the electric drive loss power is determined, different system parameters, electric control current and motor working conditions are fully considered, the loss power of parts in the electric drive system of the working condition clustering center point is determined, and the electric drive loss power is effectively determined through the loss power of the parts, so that the accuracy of the subsequent determination of the comprehensive efficiency is ensured.

(4) The driving efficiency of the driving working condition center point and the recovery efficiency of the recovery working condition center point under different conditions can be determined by considering the electric drive loss power of the driving working condition center point and the electric drive loss power of the recovery working condition center point, and various conditions are fully considered, so that a series of parameters which are determined later are accurate, and the target system parameters are ensured to be more reliable.

(5) The gear tooth array provided by the speed reducer model can be judged whether to be reasonable, under the reasonable condition, the gear transmission precision is high, the corresponding gear transmission stability is good, the transmission ratio (speed ratio) and the motor working condition can be calculated, and the electric control current corresponding to the electric drive system loss model is determined; in the case of an unreasonable gear tooth array, problems of poor bearing capacity of the gear and severe shock and vibration may occur, so that the number of teeth in the updated gear tooth array may be modified.

It should be noted that, the technical effects caused by any implementation manner of the second aspect to the fifth aspect may refer to the technical effects caused by the corresponding implementation manner in the first aspect, which are not described herein.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application and do not constitute a undue limitation on the application.

FIG. 1 is a schematic diagram illustrating a configuration of an electro-drive system parameter determination apparatus according to an exemplary embodiment;

FIG. 2 is a flowchart illustrating a method of determining parameters of an electric drive system, according to an example embodiment;

FIG. 3 is a schematic diagram illustrating a cluster of driving conditions, according to an example embodiment;

FIG. 4 is a schematic diagram illustrating a recovery condition cluster, according to an example embodiment;

FIG. 5 is a flowchart illustrating yet another method of determining parameters of an electric drive system, according to an exemplary embodiment;

FIG. 6 is a schematic diagram of a software control policy table shown in accordance with an exemplary embodiment;

FIG. 7 is a schematic diagram of yet another software control policy table shown in accordance with an exemplary embodiment;

FIG. 8 is a schematic diagram of a three-phase half-bridge power inverter shown according to an exemplary embodiment;

FIG. 9 is a schematic diagram illustrating a motor loss according to an exemplary embodiment;

FIG. 10 is a flow chart illustrating a loss of retarder power according to an exemplary embodiment;

FIG. 11 is a flowchart illustrating yet another method of determining parameters of an electric drive system, according to an exemplary embodiment;

FIG. 12 is a block diagram illustrating an electro-drive system parameter determination apparatus, according to an example embodiment;

Fig. 13 is a block diagram of an electronic device, according to an example embodiment.

Detailed Description

In order to enable a person skilled in the art to better understand the technical solutions of the present application, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.

Under normal conditions, parameters of the traditional electric drive system need to consider influences of the running condition of the whole vehicle, efficiency map of a motor system, speed ratio of a speed reducer and the like, and the equipment can calculate and determine the comprehensive efficiency of each electric drive system, so that the electric drive system is evaluated and analyzed, and several modes for calculating the comprehensive efficiency are introduced.

1. The method comprises the steps of performing bench test on an electric vehicle electric drive system to obtain a drive efficiency value and a recovery efficiency value of the electric vehicle electric drive system in a drive mode and a brake mode; then, the driving efficiency value and the recovery efficiency value of the tested electric vehicle electric drive system are manufactured into an MAP, and the MAP is divided into areas; and then calculating the average efficiency of the divided areas, and finally comparing the average efficiency value and the area occupation ratio of different areas, calculating the comprehensive efficiency of the electric drive system and evaluating the advantages and disadvantages of the electric drive system.

2. And (3) obtaining an operation working condition point of the electric drive carrying vehicle through whole vehicle parameter analysis and calculation, dividing the operation working condition into a driving mode, a feeding mode and a static mode according to the electric drive operation working condition, and clustering the driving mode working condition and the feeding mode working condition by adopting a KMeans clustering calculation method to obtain a typical working condition point. Calculating the electric drive efficiency based on the typical working condition points obtained by clustering; and the comprehensive efficiency of the electric drive of the working condition of the driving mode and the working condition of the feeding mode is obtained by respectively calculating the efficiencies of all working conditions of the driving mode and the feeding mode, so that the calculation process of the electric drive efficiency is simplified, the comparison and analysis of the electric drive efficiency are convenient, and guidance is provided for the development of the operation efficiency of an electric drive system.

3. The wheel side efficiency MAP of the driving motor system is obtained by two-dimensional interpolation of the system efficiency of the bench test working condition, the total energy of the battery pack and the total energy of the wheel side consumed by the NEDC or the CLTC driving working condition are obtained by integrating time according to the direct current power and the wheel side power of each time point in the NEDC or the CLTC driving working condition, and the comprehensive efficiency of the NEDC or the CLTC driving working condition of the driving motor system is calculated, so that the efficiency of a set of driving motor system is evaluated.

4. Determining target design information, determining target transmission energy consumption meeting transmission energy consumption conditions according to the target design information, and determining target double-motor parameters and target transmission parameters according to the target transmission energy consumption so as to determine topological structure parameters of the electric drive system of the target double-motor transmission, thereby improving the accuracy of acquisition of the electric drive system of the double-motor transmission.

In summary, the current research on the efficiency test and calculation evaluation method of the electric drive system is relatively mature, but the parameter matching design period is long and is not the optimal parameter design, so that the problem of serious resource waste in product development and later scheme optimization is caused, and the research on the parameter matching method for determining key parts of the electric drive system is relatively less.

For easy understanding, the method for determining parameters of an electric drive system provided by the application is specifically described below with reference to the accompanying drawings.

Fig. 1 is a schematic structural diagram of an electric drive system parameter determination apparatus 100 according to an exemplary embodiment, which includes a system parameter determination module 101 and an acquisition module 102.

The system parameter determining module 101 may determine, for each set of electric drive system loss models, based on the driving efficiency and the recovery efficiency, a comprehensive efficiency of the electric drive system loss models to obtain a comprehensive efficiency of each set of electric drive system loss models in a plurality of sets of electric drive loss model combinations, and determine, according to different configurations of different models, a system parameter corresponding to a target electric drive loss model with the greatest comprehensive efficiency, where the system parameter may be understood as an optimal electric drive system parameter.

The acquisition module 102 is used for acquiring the driving efficiency and the recovery efficiency of the electric drive system loss model corresponding to the working condition clustering center point in the embodiment of the application, and sends the driving efficiency and the recovery efficiency to the system parameter determination module 101.

FIG. 2 is a flowchart illustrating a method of determining parameters of an electric drive system, according to an exemplary embodiment, as shown in FIG. 2, comprising the steps of:

s201, determining working condition clustering center points of multiple groups of electric drive system loss models.

The system loss models of the electric drive system comprise a plurality of loss models, system parameters in any two groups of electric drive system loss models are different, the working condition clustering center point comprises a driving working condition center point and a recovery working condition center point, and the working condition clustering center point is the center point of the working condition point of the electric drive assembly, which is determined by a clustering algorithm.

In one possible implementation manner, the electric driving system parameter determining device calculates the corresponding rotation speed N and torque T of the electric driving work under a plurality of moments corresponding to the driving working condition (CHINA LIGHT-duty VEHICLE TEST CYCLE, CLTC) of the chinese light vehicle or the testing circulating working condition (World LIGHT VEHICLE TEST CYCLE, WLTC) of the light vehicle based on the whole vehicle dynamics equation, and the electric driving system parameter determining device may divide the working condition into a plurality of electric driving assembly working condition points (N, T), for example 36000 electric driving assembly working condition points, and divide the plurality of electric driving assembly working condition points into three types according to the torque and rotation speed of the plurality of electric driving assembly working condition points, namely a driving working condition point, a recovering working condition point and a static working condition point.

Furthermore, the electric drive system parameter determining device clusters the driving working condition point and the recovery working condition point through a K-means clustering algorithm to obtain a driving working condition center point of the driving working condition point and a recovery working condition center point of the recovery working condition point.

For example, the rotational speeds N of the electric drive operation at a plurality of times satisfy the following formula 1:

wherein u is the vehicle speed (m/s); r is the wheel radius (m).

The torque T of the electric drive operation at a plurality of times satisfies the following equation 2:

Wherein g is the gravitational acceleration (m/s 2); m is the mass (kg) of the whole vehicle; alpha is gradient (°); f is the rolling resistance coefficient; a is the windward area (m 2); c _D is the air resistance coefficient; ua is the vehicle speed (km/h); delta is the conversion coefficient of the rotating mass of the automobile.

As shown in fig. 3, the parameter determining device for an electric drive system in the embodiment of the application clusters the driving working condition points through a K-means clustering algorithm to obtain three driving working condition center points. Specifically, driving operating center point D ₁(N₁,T₁), driving operating center point D ₂(N₂,T₂), driving operating center point D ₃(N₃,T₃), driving operating center point D ₁(N₁,T₁) has a weight ratio of D ₁, driving operating center point D ₂(N₂,T₂) has a weight ratio of D ₂, and driving operating center point D ₃(N₃,T₃) has a weight ratio of D ₃.

Further, as shown in fig. 4, the parameter determining device of the electric drive system clusters the recovery working condition points through a K-means clustering algorithm to obtain three recovery working condition center points. Specifically, recovery center point D ₄(N₄,T₄), recovery center point D ₅(N₅,T₅), recovery center point D ₆(N₆,T₆), recovery center point D ₄(N₄,T₄) has a weight ratio of b ₁, recovery center point D ₅(N₅,T₅) has a weight ratio of b ₂, and recovery center point D ₆(N₆,T₆) has a weight ratio of b ₃.

S202, aiming at each group of electric drive system loss models, obtaining the efficiency of working condition clustering center points of the electric drive system loss models.

The efficiency of the driving working condition center point is driving efficiency, and the efficiency of the recovery working condition center point is recovery efficiency.

By way of example, the electric drive loss model combination may be composed of an electric control loss model Ka, a motor loss model Pa, a speed reducer loss model Qa, or an electric control loss model Ka, a motor loss model Pb, a speed reducer loss model Qb, or an electric control loss model Ka, a motor loss model Pb, a speed reducer loss model Qc, or the like, so that it is known that the multiple groups of electric drive loss model combinations are determined by traversing combinations of K electric control loss models, P motor loss models, and Q speed reducer loss models.

The electric drive system loss model composed of the electric control loss model Ka, the motor loss model Pa and the speed reducer loss model Qa is taken as an example.

In combination with the example in S201, the electric drive system parameter determining device obtains the efficiency of the driving condition center point D ₁, the driving condition center point D ₂, the driving condition center point D ₃, the recovery condition center point D ₄, the recovery condition center point D ₅, and the recovery condition center point D ₆ of the electric drive system loss model formed by the electric control loss model Ka, the motor loss model Pa, and the speed reducer loss model Qa.

The driving efficiency of the driving working condition center point may be an average driving efficiency η _d of the driving working condition center points, and the driving efficiency η _d may satisfy the following formula 3:

η _d＝W_{d_out}/W_{d_in} equation 3

Where W _d-out is drive output energy and W _d-in is drive input energy.

The recovery efficiency of the recovery operating center point may be an average recovery efficiency η _b of the plurality of recovery operating center points, and the recovery efficiency η _b may satisfy the following equation 4:

η _b＝W_{b_out}/W_{b_in} equation 4

Wherein W _b-out is recovered output energy, and W _b-in is recovered input energy.

S203, determining the comprehensive efficiency of the loss model of the electric drive system based on the driving efficiency and the recovery efficiency, so as to obtain the comprehensive efficiency of each group of loss models of the electric drive system in the combination of multiple groups of loss models of the electric drive system.

In combination with the example in S202, the comprehensive efficiency η of the electric drive system loss model may satisfy the following equation 5:

Furthermore, the electric drive system parameter determining device can calculate the comprehensive efficiency of each electric drive system loss model in the plurality of groups of electric drive loss model combinations through the formula 5.

It can be understood that the electric control loss model, the motor loss model and the speed reducer loss model in each group of electric drive loss model combinations are different, so that the system parameters provided by the electric control loss model, the motor loss model and the speed reducer loss model are different, and further the comprehensive efficiency determined by calculation of each group of electric drive loss model combinations is different.

S204, determining target system parameters according to the comprehensive efficiency of each group of electric drive system loss models in the combination of the plurality of groups of electric drive loss models.

The target system parameters are system parameters corresponding to a target electric drive loss model with the greatest comprehensive efficiency in a plurality of groups of electric drive loss model combinations, and the target system parameters are used for adjusting an electric drive system of the vehicle.

As a possible implementation manner, the electric drive system parameter determining device may determine the target electric drive loss model according to the comprehensive efficiency of each group of electric drive system loss models in the multiple groups of electric drive loss model combinations, and further, the electric drive system parameter determining device uses the system parameter corresponding to the target electric drive loss model as the target system parameter, and adjusts the electric drive system of the vehicle through the target system parameter.

It should be noted that the specific calculation modes of the respective parameters involved in S201 to S204 are described in detail above. The foregoing description is provided to more clearly describe the method for determining parameters of an electric drive system according to the embodiments of the present disclosure, and should not be construed as limiting the specific implementation of the present disclosure.

Based on the technical scheme of fig. 2, the method for determining parameters of an electric driving system provided by the embodiment of the application not only can obtain the efficiency of the working condition clustering center point of the electric driving system loss model aiming at each group of electric driving system loss models, and determine the comprehensive efficiency of the electric driving system loss models through the efficiency, but also can use the system parameters corresponding to the electric driving loss models in each group of electric driving loss model combination as the target system parameters by adjusting the electric driving system of the vehicle through the target system parameters, so that the system parameters provided by the electric control loss models, the motor loss models and the speed reducer loss models are different, and further the comprehensive efficiency determined by calculating the electric driving loss model combination in each group of electric driving loss model combination is different, thereby ensuring the accuracy of the comprehensive efficiency determined by each group of electric driving loss model combination, and further the electric driving system parameter determining device can determine the target electric driving loss model according to the comprehensive efficiency of each group of electric driving system loss models in the electric driving loss model combination, further, and the system parameters corresponding to the target electric driving loss model are used as the target system parameters, and the electric driving system of the vehicle is adjusted through the target system parameters, so that the acceptance of high efficiency indexes of the electric driving system is supported, and the user experience is improved.

In some embodiments, in order to obtain efficiency of the working condition clustering center point of the loss model of the electric drive system, as shown in fig. 5, the method for determining parameters of the electric drive system provided by the embodiment of the application further includes the following steps:

S501, acquiring electric control current and system parameters of a working condition clustering center point of an electric drive system loss model.

The electric control current is determined according to motor working conditions, wherein the motor working conditions comprise a rotating speed working condition and a torque working condition.

As a possible implementation manner, the electric drive system parameter determining device may determine a gear tooth array of the speed reducer according to the speed reducer model in the electric drive system loss model, and in the case that the gear tooth array meets the preset condition, the electric drive system parameter determining device determines a motor working condition corresponding to the electric drive system loss model based on the gear tooth array, and further the electric drive system parameter determining device determines an electric control current corresponding to the electric drive system loss model according to the motor working condition.

The preset condition is that the number of each gear in the gear tooth array is larger than a threshold value, the transmission ratio of a secondary gear in the gear tooth array is larger than that of a primary gear, and one speed reducer model corresponds to one gear tooth array.

In combination with the example in S202, the electric drive system parameter determination means determines a gear number combination (Z ₁,Z₂,Z₃,Z₄) from the decelerator loss model Qa in the electric drive system loss model (electric control loss model Ka, motor loss model Pa, decelerator loss model Qa), where Z ₁,Z₂,Z₃,Z₄ is the number of teeth of the gear, whereIn the case of (2), the electric drive system parameter determining means determines that the gear tooth array does not satisfy the preset condition, and conversely, the electric drive system parameter determining means determines that the gear tooth number satisfies the preset condition, and the electric drive system parameter determining means may determine the transmission ratio i according to the following formula 6.

Furthermore, the parameter determining device of the electric drive system can determine the rotating speed working condition N _m and the torque working condition T _m of the motor according to the formula 7;

Wherein T _i is the torque of the ith working condition clustering center point, and N _i is the rotating speed of the ith working condition clustering center point. For example, the torque T ₁ and the rotation speed N ₁ of the driving condition center point D ₁ are brought into the formula 7, the torque condition and the rotation speed condition (motor condition) of the motor that obtains the driving condition center point D ₁ are determined, and the electric driving system parameter determining device obtains the electric control working current I _S1 of the driving condition center point D ₁ according to the torque condition and the rotation speed condition of the motor that drives the condition center point D ₁, in combination with a software control ammeter, as shown in fig. 6 and fig. 7.

Correspondingly, the electric drive system parameter determining device can calculate and obtain the electric control working current I _S2 of the driving working condition central point D ₂, the electric control working current I _S3 of the driving working condition central point D ₃, the electric control working current I _S4 of the recovery working condition central point D ₄, the electric control working current I _S5 of the recovery working condition central point D ₅ and the electric control working current I _S6 of the recovery working condition central point D ₆ through a formula 7.

For example, the electric drive system parameter determining device may obtain system parameters provided by an electric drive system loss model (an electric control loss model Ka, a motor loss model Pa, and a speed reducer loss model Qa), for example, a loss calculation coefficient provided by the electric control loss model Ka is (k ₁,k₂,k₃), an electromagnetic scheme parameter provided by the motor loss model Pa is (R _s,g₁,g₂,g₃,q₁,q₂), and a gear parameter provided by the speed reducer loss model Qa is (z ₁,z₂,z₃,z₄).

As yet another possible implementation, the number of teeth in the gear tooth array is updated in case the gear tooth array does not meet a preset condition.

Another example, inIf the electric drive system parameter determining device determines that the gear tooth array does not meet the preset condition, the speed reducer loss model can be replaced or the gear parameters in the speed reducer loss model Qa can be modified.

S502, determining the electric drive loss power corresponding to the working condition clustering center point based on the electric control current, the system parameters and the working condition of the motor.

The system parameters comprise electric control loss parameters corresponding to the electric control loss model, motor loss parameters corresponding to the motor loss model and reducer loss parameters corresponding to the reducer loss model.

In one possible implementation manner, the electric drive system parameter determining device determines electric control loss power, motor loss power and speed reducer loss power of the working condition clustering center point based on the electric control current, the system parameter and the motor working condition, and further, the electric drive system parameter determining device can take the sum of the electric control loss power, the motor loss power and the speed reducer loss power as the electric drive loss power.

The electric drive loss power comprises electric drive loss power of a driving working condition center point and electric drive loss power of a recovery working condition center point.

In combination with the example in S501, the electric control loss power P _IGBT of the working condition cluster center point satisfies the following formula 8

Wherein, (k ₁,k₂,k₃) is a loss calculation coefficient provided by an electric control loss model Ka, I _S is electric control current corresponding to a working condition clustering center point, V _co is constant tube voltage drop of the IGBT, R _co is equivalent resistance when the IGBT is conducted, and V _fo is diode voltage drop; r _fo is the equivalent resistance of the diode when the diode is turned on, E _on、E_off fits the on energy fitting coefficient a _on,b_on,c_on with the diode reverse recovery energy, the off energy fitting coefficient a _off,b_off,c_off, the diode reverse recovery energy fitting coefficient a _rec,b_rec,c_rec,U_nom is the reference voltage, and the on, off and diode loss temperature coefficients are ρ _on,ρ_off,ρ_rec respectively.

It can be appreciated that the electric drive system parameter determining device only needs to substitute the electric control current corresponding to each working condition clustering center point into the formula 8, so that the driving working condition center point D ₁(N₁,T₁), the driving working condition center point D ₂(N₂,T₂), the driving working condition center point D ₃(N₃,T₃), the recovery working condition center point D ₄(N₄,T₄), the recovery working condition center point D ₅(N₅,T₅), and the recovery working condition center point D ₆(N₆,T₆) corresponding to the electric control loss power P _IGBT can be determined.

The motor loss power P _mot of the working condition clustering center point meets the following formula 9

Wherein N _m is the motor rotating speed working condition corresponding to the working condition clustering center point, R _s represents the equivalent resistance of each winding, I _s represents the effective value of phase current, g ₁、g₂、g₃ represents the iron loss fitting coefficient, hysteresis loss coefficient P _h and ρ represents the iron core density; sigma represents the conductivity of the iron core silicon steel sheet, d represents the thickness of the silicon steel sheet, S represents the sectional area of the silicon steel sheet, G, V ₀ is the material coefficient of the silicon steel sheet, P _n is the pole pair number, and the mechanical loss coefficient q ₁、q₂.

Correspondingly, the electric drive system parameter determining device may determine a driving working condition center point D ₁(N₁,T₁), a driving working condition center point D ₂(N₂,T₂), a driving working condition center point D ₃(N₃,T₃), a recovery working condition center point D ₄(N₄,T₄), a recovery working condition center point D ₅(N₅,T₅), and a recovery working condition center point D ₆(N₆,T₆).

The loss power P _reducer of the speed reducer at the working condition clustering center point can meet the following formula 10

P _reducer＝f(z₁,z₂,z₃,z₄,N_m,T_m) equation 10

Wherein N _m is the motor rotation speed working condition corresponding to the working condition clustering center point, and T _m is the motor torque working condition corresponding to the working condition clustering center point. Correspondingly, the electric drive system parameter determining device may determine a driving operating center point D ₁(N₁,T₁), a driving operating center point D ₂(N₂,T₂), a driving operating center point D ₃(N₃,T₃), a recovery operating center point D ₄(N₄,T₄), a recovery operating center point D ₅(N₅,T₅), and a recovery operating center point D ₆(N₆,T₆).

Furthermore, the driving working condition central point D ₁, the driving working condition central point D ₂, the driving working condition central point D ₃, the recovery working condition central point D ₄, the recovery working condition central point D ₅, the electric control loss power, the motor loss power and the speed reducer loss power corresponding to the recovery working condition central point D ₆ can be substituted into the formula P _loss＝P_IGBT+P_mot+P_reducer by the electric driving system parameter determining device, and the electric driving loss power P _loss of each working condition clustering central point is determined.

S503, determining efficiency of working condition clustering center points of an electric drive system loss model based on electric drive loss power.

In one possible implementation manner, the parameter determining device of the electric driving system may determine the driving input energy and the driving output energy according to the electric driving loss power of the driving working condition center point, and use the ratio of the driving input energy and the driving output energy as the driving efficiency of the driving working condition center point.

It can be understood that after the hardware schemes of the electric control, the motor and the speed reducer are timed, i.e. the electric driving scheme is determined, the loss power of the motor is related to the rotating speed and the torque, and then P _{loss_i}＝f(N_i,T_i), i.e. the electric driving loss power of the ith working condition cluster center point is related to the rotating speed and the torque of the ith working condition cluster center.

For example, the electric drive system parameter determination device may determine the driving efficiency of the driving condition center point through equation 11-equation 15. Specifically, the electric driving system parameter determining device determines output power P _i corresponding to a driving working condition central point D ₁, a driving working condition central point D ₂ and a driving working condition central point D ₃.

P _i＝N_iT_i/9550 equation 11

Wherein P _i is the output power of the ith driving working condition center point.

Drive input power P _in-i:

p _{in_i}＝Pl_{oss_i}+P_i equation 12

Wherein, P _in-i is the driving input power of the ith driving working condition center point, P _loss-i is the electric driving loss power of the ith driving working condition center point, and P _i is the output power of the ith driving working condition center point.

Drive input energy W _d-in:

W _{d_in}＝∫(P_in1d₁+P_in2d₂+P_in3d₃) dt formula 13

Wherein, P _in1 is the driving input power of the driving condition center point D ₁, D ₁ is the weight ratio of the driving condition center point D ₁, P _in2 is the driving input power of the driving condition center point D ₂, D ₂ is the weight ratio of the driving condition center point D ₂, P _in3 is the driving input power of the driving condition center point D ₃, and D ₃ is the weight ratio of the driving condition center point D ₃.

Drive output energy W _d-out:

W _{d_out}＝∫(P₁d₁+P₂d₂+P₃d₃) dt formula 14

Wherein, P ₁ is the output power of the driving working condition center point D ₁, P ₂ is the output power of the driving working condition center point D ₂, and P ₃ is the output power of the driving working condition center point D ₃.

Average driving efficiency η _d:

η _d＝W_{d_out}/W_{d_in} equation 15

In summary, the electric drive system parameter determining device calculates the driving efficiency of the driving working condition center point.

In yet another possible implementation manner, the parameter determining device of the electric drive system may determine the recovered input energy and the recovered output energy according to the electric drive loss power of the recovered working condition center point, and use the ratio of the recovered input energy and the recovered output energy as the recovery efficiency of the recovered working condition center point.

As yet another example, the electric drive system parameter determination device may determine the recovery efficiency of the recovery operating center point via equation 16-equation 20. Specifically, the parameter determining device of the electric drive system determines input power P _i corresponding to the recovery working condition central point D ₄, the recovery working condition central point D ₅ and the recovery working condition central point D ₆, and calculates input power P ₄、p₅、p₆ of the feed working condition clustering central point (recovery working condition central point).

P _i＝N_iT_i/9550 equation 16

Wherein P _i is the input power of the ith recovery operating mode center point.

Recovery output power P _out-i:

p _{out_i}＝P_i-P_{loss_i} equation 17

Wherein, P _out-i is the driving input power of the ith recovery working condition center point, P _loss-i is the electric driving loss power of the ith recovery working condition center point, and P _i is the input power of the ith recovery working condition center point.

Recovery of output energy W _b-out:

w _{b_out}＝∫(P_out1b₁+P_out2b₂+P_out3b₃) dt formula 18

Wherein, P _out1 is the recovered output power of the recovered working condition center point D ₄, b ₁ is the weight ratio of the driving working condition center point D ₄, P _out2 is the recovered output power of the recovered working condition center point D ₅, b ₂ is the weight ratio of the driving working condition center point D ₅, P _out3 is the recovered output power of the recovered working condition center point D ₆, and b ₃ is the weight ratio of the driving working condition center point D ₆.

Recovery of input energy W _b-in:

W _{b_in}＝∫(P₄b₁+P₅b₂+P₆b₃) dt formula 19

Wherein, P ₄ is the input power of the driving working condition center point D ₄, P ₅ is the input power of the driving working condition center point D ₅, and P ₆ is the input power of the driving working condition center point D ₆.

Average recovery efficiency η _b:

η _b＝W_{b_out}/W_{b_in} equation 20

In conclusion, the electric drive system parameter determining device calculates the drive efficiency of the recovery working condition center point.

Based on the technical scheme of fig. 5, the embodiment of the application provides a method for determining parameters of an electric drive system, which can determine the efficiency of working condition clustering center points of a loss model of the electric drive system, provide guidance for development and design of the electric drive system, aim at carrying out rapid matching optimization design on parameters of the electric drive system with efficient electric drive design as a target, and shorten the development period of the electric drive.

It can be understood that the electric control loss model, the motor loss model and the speed reducer loss model in the embodiment of the application are all models which are established in advance, and the establishment of a plurality of models is briefly described below.

1. The electric control loss model, as the name implies, is a loss model of a motor controller, as shown in fig. 8, is currently applied to a three-phase half-bridge power inverter, and the inverter mainly comprises an insulated bipolar transistor (Insulated Gate Bipolar Translator, IGBT) and a freewheeling diode, and the loss generated by each IGBT is the same and the loss generated by each freewheeling diode is the same assuming that each period. The loss of the IGBT in the switching state is conduction loss, switching-on loss and switching-off loss, the conduction loss of the IGBT chip is calculated, and the conduction voltage drop V _c (t) and the output current I _c (t) are approximately considered to be linear relations as shown in formula I:

v _c(t)＝V_co+R_coI_c (t) equation I

Wherein V _co is the constant tube voltage drop of the IGBT; r _co is the equivalent resistance when the IGBT is on.

The conduction loss is the integral of the voltage-current product with respect to time as shown in formula two:

P _{IGBT_con}(t)＝∫V_co(t)I_c (t) dt formula II

The average power loss of the GBT chip conducted in one current period is calculated as formula three:

wherein I _s represents phase current, M represents modulation ratio, Representing the power factor angle.

The diode conduction loss is calculated, and the linear relation existing between the conduction voltage drop V _f (t) of the diode and the current I _f (t) is as shown in formula four:

V _f(t)＝V_fo+R_foI_f (t) equation four

Wherein V _fo is diode drop; r _fo is the equivalent resistance of the diode when it is on.

The conduction loss is the integral of the voltage-current product with respect to time as in equation five:

p _{Doide_con}(t)＝∫V_fo(t)I_f (t) dt formula five

The average power loss of the diode conducted in one current period is calculated as shown in the formula six:

And calculating the switching loss of the IGBT, wherein a polynomial can be obtained by fitting according to a data manual so as to establish a mathematical model, and the mathematical model is specifically represented by the following formula seven:

wherein, the switching energy E _on、E_off of the IGBT chip and the reverse recovery energy of the diode

E _rec, a, b and c are fitting coefficients.

The average switching loss under the IGBT switching period is as follows:

Wherein f _sw is the switching frequency, U _dc is the bus voltage, and U _nom is the IGBT manual reference voltage.

The total loss of the ρ temperature coefficient IGBT in the eighth formula is as shown in the ninth formula:

P _IGBT＝6(P_{IGBT_con}+P_{Diode_con}+P_sw) equation nine

It is assumed that the M modulation ratio,The power factor angle, the f _sw switching frequency, the U _dc busbar voltage is a fixed value, and the IGBT loss can be approximately fitted into a mathematical simulation model, wherein the k1, k2 and k3 coefficients are different according to the IGBT modules. The total loss of the electronic control is as follows: /(I)

2. The motor loss model, the composition of motor loss is as shown in fig. 9, mainly includes copper loss, iron loss and mechanical loss, and wherein, copper loss calculates, when the electric current flows through motor winding, receives motor wire winding resistance's influence, and the power of loss is directly proportional with the square of electric current, can see formula ten:

P _cu＝1.5I_s ²R_s formula ten

Wherein R _s represents the equivalent resistance of each winding; i _s represents the effective value of the phase current.

The iron loss calculation, bertotti iron loss model, includes hysteresis loss P _h, eddy current loss P _c and stray loss P _e, see formula eleven:

p _Fe＝P_h+P_c+P_e formula eleven

The hysteresis loss per unit mass p _h is as the formula twelve:

Wherein f represents the frequency of the magnetic density change; k _h denotes a hysteresis loss coefficient; b _m represents the magnetic density magnitude; k (B _m) represents a hysteresis loss calculation parameter; alpha represents the hysteresis loss increase coefficient.

The eddy current loss per unit mass p _c is as in formula thirteen:

Wherein ρ represents the core density; sigma represents the conductivity of the silicon steel sheet of the iron core; t represents the variation period of magnetic density; d represents the thickness of the silicon steel sheet.

The unit mass spurious loss p _e is as in formula fourteen:

wherein S represents the sectional area of the silicon steel sheet; G. v0 is the coefficient of the silicon steel sheet material.

Assuming that the magnetic flux is sinusoidal, the flux density is consistent with the waveform of the magnetic flux. I.e.

B (t) =b _m sin (2pi ft), the simplified core loss is the formula fifteen:

Assuming that the scheme timing core loss can be approximately fitted to a mathematical model related to rotational speed and current as formula sixteen:

the mechanical loss of the motor comprises two parts, namely wind friction loss and bearing friction loss, and the wind friction loss can be represented by the following formula seventeen:

Wherein C _f represents a friction coefficient; ρ ₀ represents the ambient gas density; a represents the surface roughness of the rotor in contact with the gas; r represents the rotor radius; l represents the rotor axial length; omega _m denotes the rotor angular velocity.

Bearing friction loss calculation formula eighteen:

Wherein F represents the bearing load; p _z denotes rolling bearing friction loss; v represents the circumferential velocity at the center of the ball; the degree d represents the diameter of the ball at the center

The mechanical loss is nineteen in formula:

P _m＝P_s+P_z＝q₁N³+q₂ N formula nineteen

The total motor loss may be:

3. In a loss model of the speed reducer, as shown in fig. 10, when the transmission system works normally, the output shaft of the motor inputs power to the high-speed shaft of the speed reducer, the power is transmitted to the primary reduction driving pinion, the primary reduction driving pinion is meshed with the primary reduction driven large gear to generate primary meshing loss, oil stirring loss and windage loss, the intermediate shaft is driven by the driven gear to rotate, meanwhile, the secondary reduction driving pinion also generates oil stirring loss and windage loss, and the secondary reduction driving pinion is meshed with the secondary reduction driven large gear to generate secondary meshing loss and drive the secondary reduction driving pinion to rotate, so that oil stirring loss and windage loss are generated.

Specifically, the engagement power loss is calculated, and the average efficiency is calculated as formula twenty and formula twenty-one:

Wherein z ₁、z₂ is the number of teeth of the primary reduction pinion and the number of teeth of the large gear respectively, z ₃、z₄ is the number of teeth of the secondary reduction pinion and the number of teeth of the large gear respectively, and alpha _t、β、β_b is the end face pressure angle, the helix angle and the base circle helix angle (°) of the gear respectively; b _min is the smaller tooth width value (mm) in the meshing gear pair, f _m is the sliding friction coefficient, m _n is the normal surface modulus, Is the normal addendum coefficient.

The power lost to gear mesh is as the formula twenty-two:

Wherein: p _{E1_in}、P_{E2_in} is the input power (kW) of the first-stage reduction driving gear and the second-stage reduction driving gear respectively; η _E1、η_E2 is the meshing efficiency of the first-stage and second-stage reduction gear pair respectively.

Specifically, the oil stirring power is lost, the speed reducer is lubricated by oil immersion, and the secondary speed reduction large gear is immersed into an oil pool for a certain depth. The oil stirring loss is mainly generated by stirring lubricating oil by an operating element in the speed reducer, and is related to the rotation speed of the oil stirring element, the oil immersion depth, the lubricating oil temperature and other factors. The built churning loss model comprises the following steps: loss P _C1 caused by friction between the shaft and lubricating oil; loss P _C2 generated in the process of splashing lubricating oil on the tooth side; the loss P _C3 generated by stirring oil liquid by gear teeth. The power of the churning loss generated by each churning element is as follows:

Wherein: PM is churning power loss (kW); f _g is the gear immersion coefficient; v is the kinematic viscosity (cSt) of the lubricating oil at operating temperature; n is the element rotation speed (r/min); beta is the helical angle of the helical gear, and when beta is smaller than 10 degrees, the beta value is usually 10 degrees; l is the contact length (mm) of the element with lubricating oil; a _g is the assembly constant, typically 0.2; b is the width (mm) of the oil stirring gear; d ₀ is the element outer diameter (mm); r _f is a roughness factor.

The wind resistance power loss calculation formula is as formula twenty-four:

Wherein: p _W is wind resistance power loss (kW); μ is the dynamic viscosity (cP) of the oil mist in the reducer; b _x is the rotating element width (mm); r _x is the radius (mm) of the rotating element, and if a gear is used, the diameter of the reference circle is represented; n _x is the rotating element speed (r/min).

The gear is used as a standard component, and the corresponding parameters can be calculated after the number of teeth is determined, so the loss of the speed reducer can be expressed as a function of the input rotation speed N and torque T and the number of teeth z ₁、z₂、z₃、z₄ of the gear, P _reducer＝f(z₁,z₂,z₃,z₄, N and T).

In summary, the embodiment of the application establishes the loss model of the electric drive system.

The overall flow of the embodiment of the present application is briefly summarized below, and specifically may be shown in fig. 11, firstly, the electric drive system parameter determining device may divide the working condition into a plurality of electric drive assembly working condition points (N, T) according to a preset time interval (0.05 s), and cluster the driving working condition points and the recovery working condition points through a K-means clustering algorithm, so as to determine a clustering center and a weight, further, the electric drive system parameter determining device determines a gear tooth array of the speed reducer according to a speed reducer model in the electric drive system loss model, determine whether the number of teeth is reasonable, if so, calculate a speed ratio i, determine a rotational speed working condition N _m and a torque working condition T _m of the motor based on the speed ratio i, then the electric drive system parameter determining device may determine motor loss efficiency and speed reducer loss efficiency, determine electric control loss efficiency, add the three, calculate and determine a comprehensive efficiency (electric drive efficiency) of the electric drive system parameter determining device may determine a target system parameter according to a comprehensive efficiency of each group of electric drive system loss models in a plurality of groups of electric drive loss model combinations.

The foregoing description of the solution provided by the embodiments of the present application has been mainly presented in terms of a method. In order to achieve the above functions, the electro-drive system parameter determining device or the electronic apparatus includes a hardware structure and/or a software module for performing the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

According to the method, the function modules of the electric driving system parameter determining device or the electronic device can be divided, for example, the electric driving system parameter determining device or the electronic device can comprise each function module corresponding to each function division, or two or more functions can be integrated in one processing module. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, in the embodiment of the present application, the division of the modules is schematic, which is merely a logic function division, and other division manners may be implemented in actual implementation.

Fig. 12 is a block diagram illustrating an electro-drive system parameter determination apparatus according to an example embodiment. Referring to fig. 12, the electric drive system parameter determining apparatus 1200 includes: a processing unit 1202 and an acquisition unit 1201; a processing unit 1202, configured to determine a working condition cluster center point of the multiple groups of electric drive system loss models; the system parameters in any two groups of electric drive system loss models are different, and the working condition clustering center points comprise a driving working condition center point and a recovery working condition center point; the working condition clustering center point is a center point determined by the working condition of the electric drive assembly through a clustering algorithm; an obtaining unit 1201, configured to obtain, for each group of loss models of the electric drive system, efficiency of a working condition clustering center point of the loss models of the electric drive system; the efficiency of the driving working condition center point is driving efficiency, and the efficiency of the recovery working condition center point is recovery efficiency; the processing unit 1202 is further configured to determine, based on the driving efficiency and the recovery efficiency, a comprehensive efficiency of the electric drive system loss model, so as to obtain a comprehensive efficiency of each set of electric drive system loss models in the combination of the plurality of sets of electric drive loss models; the processing unit 1202 is further configured to determine a target system parameter according to the comprehensive efficiency of each set of electric drive system loss models in the plurality of sets of electric drive loss model combinations; the target system parameters are system parameters corresponding to a target electric drive loss model with the greatest comprehensive efficiency in the combination of the plurality of groups of electric drive loss models; the target system parameter is used to adjust an electric drive system of the vehicle.

In a possible implementation manner, the obtaining unit 1201 is further configured to obtain an electric control current and a system parameter of a working condition cluster center point of the electric drive system loss model; the electric control current is determined according to the working condition of the motor; the motor working conditions comprise a rotating speed working condition and a torque working condition; the processing unit 1202 is further configured to determine an electric drive loss power corresponding to the working condition clustering center point based on the electric control current, the system parameter and the working condition of the motor; the system parameters comprise electric control loss parameters corresponding to the electric control loss model, motor loss parameters corresponding to the motor loss model and reducer loss parameters corresponding to the reducer loss model; the processing unit 1202 is further configured to determine efficiency of the operating mode cluster center point of the loss model of the electric drive system based on the electric drive loss power.

In a possible implementation manner, the processing unit 1202 is specifically configured to: determining electric control loss power, motor loss power and reducer loss power of a working condition clustering center point based on electric control current, system parameters and motor working conditions; and taking the sum of the electric control loss power, the motor loss power and the reducer loss power as the electric drive loss power.

In one possible embodiment, the electric drive loss power comprises an electric drive loss power driving a center point of the operating condition; the processing unit 1202 is specifically configured to: determining driving input energy and driving output energy according to the electric driving loss power of the driving working condition center point; and taking the ratio of the driving input energy to the driving output energy as the driving efficiency of the driving working condition center point.

In one possible embodiment, the electric drive loss power further comprises recovering the electric drive loss power of the operating center point; the processing unit 1202 is specifically configured to: according to the electric drive loss power of the center point of the recovery working condition, the recovery input energy and the recovery output energy are determined; and taking the ratio of the recovered input energy to the recovered output energy as the recovery efficiency of the recovery working condition center point.

In a possible implementation, the processing unit 1202 is further configured to: determining a gear tooth array of the speed reducer based on a speed reducer model in the electric drive system loss model; under the condition that the gear tooth array meets the preset condition, determining the motor working condition corresponding to the electric drive system loss model based on the gear tooth array; the preset condition is that the number of teeth of each gear in the gear tooth array is larger than a threshold value, and the transmission ratio of a secondary gear in the gear tooth array is larger than that of a primary gear; and determining the electric control current corresponding to the loss model of the electric drive system according to the working condition of the motor.

In a possible implementation, the processing unit 1202 is further configured to: and updating the number of teeth in the gear tooth array under the condition that the gear tooth array does not meet the preset condition.

The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.

Fig. 13 is a block diagram of an electronic device, according to an example embodiment. As shown in fig. 13, electronic device 1300 includes, but is not limited to: a processor 1301, and a memory 1302.

The memory 1302 is used for storing executable instructions of the processor 1301. It will be appreciated that the processor 1301 is configured to execute instructions to implement the method of determining parameters of the electric drive system in the above embodiment.

It should be noted that the electronic device structure shown in fig. 13 is not limited to the electronic device, and the electronic device may include more or less components than those shown in fig. 13, or may combine some components, or may have different arrangements of components, as will be appreciated by those skilled in the art.

Processor 1301 is a control center of the electronic device, connects various parts of the entire electronic device using various interfaces and lines, and performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in memory 1302, and calling data stored in memory 1302, thereby performing overall monitoring of the electronic device. Processor 1301 may include one or more processing units. Alternatively, processor 1301 may integrate an application processor that primarily handles operating systems, user interfaces, applications, etc., with a modem processor that primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 1301.

The memory 1302 may be used to store software programs as well as various data. The memory 1302 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, application programs (such as a determination unit, a processing unit, etc.) required for at least one functional module, and the like. In addition, memory 1302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.

In an exemplary embodiment, a computer readable storage medium is also provided, such as a memory 1302 including instructions executable by the processor 1301 of the electronic device 1300 to implement the method in the above-described embodiment.

In actual implementation, the functions of the acquiring unit 1201 and the processing unit 1202 in fig. 12 may be implemented by the processor 1301 in fig. 13 calling a computer program stored in the memory 1302. For specific implementation, reference may be made to the description of the method in the above embodiment, and details are not repeated here.

Alternatively, the computer readable storage medium may be a non-transitory computer readable storage medium, for example, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

In an exemplary embodiment, embodiments of the application also provide a computer program product comprising one or more instructions executable by the processor 1301 of the electronic apparatus to perform the method in the above-described embodiment.

It should be noted that, when the instructions in the computer readable storage medium or one or more instructions in the computer program product are executed by the processor of the electronic device, the processes of the foregoing method embodiments are implemented, and the technical effects similar to those of the foregoing method can be achieved, so that repetition is avoided, and no further description is provided herein.

From the foregoing description of the embodiments, it will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules, so as to perform all the classification parts or part of the functions described above.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and the parts shown as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. The purpose of the embodiment scheme can be achieved by selecting part or all of the classification part units according to actual needs.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present application, or the portion contributing to the prior art or the whole classification portion or portion of the technical solution, may be embodied in the form of a software product stored in a storage medium, where the software product includes several instructions to cause a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to execute the whole classification portion or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.

The present application is not limited to the above embodiments, and any changes or substitutions within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims

1. An electric drive system parameter determination method, characterized by being applied to a vehicle, comprising:

Determining working condition clustering center points of multiple groups of electric drive system loss models; the system parameters in any two groups of electric drive system loss models are different, and the working condition clustering center points comprise a driving working condition center point and a recovery working condition center point; the working condition clustering center point is a center point determined by the working condition of the electric drive assembly through a clustering algorithm;

Aiming at each group of electric drive system loss models, obtaining the efficiency of working condition clustering center points of the electric drive system loss models; the efficiency of the driving working condition center point is driving efficiency, and the efficiency of the recovery working condition center point is recovery efficiency;

based on the driving efficiency and the recovery efficiency, determining the comprehensive efficiency of the loss model of the electric drive system to obtain the comprehensive efficiency of each group of loss models of the electric drive system in a plurality of groups of electric drive loss model combinations;

Determining target system parameters according to the comprehensive efficiency of each group of electric drive system loss models in the multiple groups of electric drive loss model combinations; the target system parameters are system parameters corresponding to a target electric drive loss model with the greatest comprehensive efficiency in the combination of the plurality of groups of electric drive loss models; the target system parameter is used for adjusting an electric drive system of the vehicle.

2. The method of claim 1, wherein the obtaining, for each set of electric drive system loss models, the efficiency of the operating condition cluster center point of the electric drive system loss models comprises:

acquiring electric control current and system parameters of a working condition clustering center point of the electric drive system loss model; the electric control current is determined according to the working condition of the motor; the motor working conditions comprise a rotating speed working condition and a torque working condition;

Determining electric drive loss power corresponding to the working condition clustering center point based on the electric control current, the system parameters and the motor working condition; the system parameters comprise electric control loss parameters corresponding to the electric control loss model, motor loss parameters corresponding to the motor loss model and reducer loss parameters corresponding to the reducer loss model;

And determining the efficiency of the working condition clustering center point of the electric drive system loss model based on the electric drive loss power.

3. The method of claim 2, wherein the determining the electric drive loss power corresponding to the operating condition cluster center point based on the electric control current, the system parameter, and the motor operating condition comprises:

Determining electric control loss power, motor loss power and speed reducer loss power of the working condition clustering center point based on the electric control current, the system parameters and the motor working condition;

and taking the sum of the electric control loss power, the motor loss power and the speed reducer loss power as the electric drive loss power.

4. The method of claim 2, wherein the electric drive loss power comprises an electric drive loss power of the drive operating mode center point;

The determining the efficiency of the working condition clustering center point of the electric drive system loss model based on the electric drive loss power comprises the following steps:

determining driving input energy and driving output energy according to the electric driving loss power of the driving working condition center point;

and taking the ratio of the driving input energy to the driving output energy as the driving efficiency of the driving working condition center point.

5. The method of claim 4, wherein the electric drive loss power further comprises an electric drive loss power of the recovery operating center point;

The method further comprises the steps of:

Determining recovered input energy and recovered output energy according to the electric drive loss power of the central point of the recovery working condition;

And taking the ratio of the recovered input energy to the recovered output energy as the recovery efficiency of the recovery working condition center point.

6. The method of claim 2, wherein the obtaining the electric current of the operating condition cluster center point of the electric drive system loss model comprises:

Determining an array of gear teeth of the retarder based on a retarder model of the electric drive system loss model;

Under the condition that the gear tooth array meets the preset condition, determining a motor working condition corresponding to the electric drive system loss model based on the gear tooth array; the preset condition is that the number of teeth of each gear in the gear tooth array is larger than a threshold value, and the transmission ratio of a secondary gear in the gear tooth array is larger than that of a primary gear;

and determining the electric control current of the working condition clustering center point of the electric drive system loss model according to the working condition of the motor.

7. The method according to claim 6, further comprising:

And updating the number of teeth in the gear tooth array under the condition that the gear tooth array does not meet the preset condition.

8. An electric drive system parameter determination apparatus, for use with a vehicle, the apparatus comprising: a processing unit and an acquisition unit;

The processing unit is used for determining working condition clustering center points of the multiple groups of electric drive system loss models; the system parameters in any two groups of electric drive system loss models are different, and the working condition clustering center points comprise a driving working condition center point and a recovery working condition center point; the working condition clustering center point is a center point determined by the working condition of the electric drive assembly through a clustering algorithm;

The acquisition unit is used for acquiring the efficiency of the working condition clustering center point of the electric drive system loss model aiming at each group of electric drive system loss models; the efficiency of the driving working condition center point is driving efficiency, and the efficiency of the recovery working condition center point is recovery efficiency;

the processing unit is further used for determining the comprehensive efficiency of the electric drive system loss model based on the driving efficiency and the recovery efficiency so as to obtain the comprehensive efficiency of each group of electric drive system loss models in the multiple groups of electric drive loss model combinations;

The processing unit is further used for determining target system parameters according to the comprehensive efficiency of each group of electric drive system loss models in the multiple groups of electric drive loss model combinations; the target system parameters are system parameters corresponding to a target electric drive loss model with the greatest comprehensive efficiency in the combination of the plurality of groups of electric drive loss models; the target system parameter is used for adjusting an electric drive system of the vehicle.

9. The device of claim 8, wherein the obtaining unit is further configured to obtain an electric control current and a system parameter of a working condition cluster center point of the electric drive system loss model; the electric control current is determined according to the working condition of the motor; the motor working conditions comprise a rotating speed working condition and a torque working condition;

The processing unit is further used for determining electric drive loss power corresponding to the working condition clustering center point based on the electric control current, the system parameters and the working condition of the motor; the system parameters comprise electric control loss parameters corresponding to the electric control loss model, motor loss parameters corresponding to the motor loss model and reducer loss parameters corresponding to the reducer loss model;

and the processing unit is also used for determining the efficiency of the working condition clustering center point of the electric drive system loss model based on the electric drive loss power.

10. The device according to claim 9, wherein the processing unit is configured to determine an electronically controlled power loss, a motor power loss, and a retarder power loss for the operating condition cluster center point based on the electronically controlled current, the system parameter, and the motor operating condition;

11. An electronic device, comprising:

A processor;

A memory for storing the processor-executable instructions;

Wherein the processor is configured to execute the instructions to implement the method of any one of claims 1 to 7.

12. A computer readable storage medium, characterized in that, when computer-executable instructions stored in the computer readable storage medium are executed by a processor of an electronic device, the electronic device is capable of performing the method of any one of claims 1 to 7.