CN117382424A - Method and device for predicting endurance mileage, vehicle and computer program product - Google Patents

Method and device for predicting endurance mileage, vehicle and computer program product Download PDF

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Publication number
CN117382424A
CN117382424A CN202311567780.3A CN202311567780A CN117382424A CN 117382424 A CN117382424 A CN 117382424A CN 202311567780 A CN202311567780 A CN 202311567780A CN 117382424 A CN117382424 A CN 117382424A
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battery
parameter
value
current moment
state
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孙平超
陈斌
彭振山
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Jidu Technology Wuhan Co ltd
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Jidu Technology Wuhan Co ltd
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Priority to CN202311567780.3A priority Critical patent/CN117382424A/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
    • B60L3/12—Recording operating variables ; Monitoring of operating variables
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/10—Vehicle control parameters
    • B60L2240/12—Speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/54—Drive Train control parameters related to batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

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  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The present disclosure relates to the field of battery technologies, and in particular, to a method and apparatus for predicting a range, a vehicle, and a computer program product. The method comprises the following steps: acquiring an average speed parameter of a target vehicle, and acquiring a state parameter of a battery to be detected in the target vehicle, a first electric energy representation value and a second electric energy representation value of the battery; obtaining a first endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the first electric energy representation value, and obtaining a second endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the second electric energy representation value; predicting a target range corresponding to the battery at the current moment based on the first range and the second range; and sending the target endurance mileage to terminal equipment for display. Because the method and the device do not calculate the range based on the energy consumption flow direction, but directly predict the target range from the energy consumption source according to the average vehicle speed parameter, the battery state parameter and the like, the prediction result is more accurate.

Description

Method and device for predicting endurance mileage, vehicle and computer program product
Technical Field
The present disclosure relates to the field of battery technologies, and in particular, to a method and apparatus for predicting a range, a vehicle, and a computer program product.
Background
For environmental protection, pollution reduction and other factors, electric energy is gradually considered in the design of vehicles, wherein the hybrid vehicles and the electric vehicles can provide power for the vehicles through batteries, and the endurance mileage of the batteries of the vehicles needs to be tested in the later stages of the production of the hybrid vehicles and the electric vehicles.
In the related art, a new standard european cycle test (New European Driving Cycle, NEDC) is often used as a standard, the mileage that the battery can still travel with the current residual electric quantity is predicted, that is, the battery is predicted according to factors such as vehicle speed, load, air conditioner, wind resistance, etc., but factors influencing the endurance mileage are too many, NEDC cannot take all factors into consideration, for example, factors such as braking feedback strategies, different road conditions, different climates, etc., so that the predicted result is often 15% to 30% higher than the actual situation.
In summary, it is inaccurate to predict battery range in the direction of the vehicle energy consumption flow.
Disclosure of Invention
The embodiment of the application provides a method, a device, a vehicle and a computer program product for predicting the endurance mileage of a battery, which are used for improving the accuracy of predicting the endurance mileage of the battery.
The method for predicting the endurance mileage provided by the embodiment of the application comprises the following steps:
acquiring an average speed parameter of a target vehicle and a state parameter of a battery to be detected in the target vehicle; wherein the state parameter is used for describing the internal state and the service condition of the battery;
acquiring a first electric energy representation value and a second electric energy representation value of the battery;
obtaining a first endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the first electric energy representation value, and obtaining a second endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the second electric energy representation value;
predicting a target range corresponding to the battery at the current moment based on the first range and the second range;
and sending the target endurance mileage to a terminal device, so that the terminal device displays the target endurance mileage on a display interface.
The embodiment of the application provides a prediction device of endurance mileage,
a first acquisition unit configured to acquire an average vehicle speed parameter of a target vehicle and a state parameter of a battery to be detected in the target vehicle; wherein the state parameter is used for describing the internal state and the service condition of the battery;
The second acquisition unit is used for acquiring a first electric energy representation value and a second electric energy representation value of the battery;
the third obtaining unit is configured to obtain a first endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the first electric energy representation value, and obtain a second endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the second electric energy representation value;
the prediction unit is used for predicting a target range corresponding to the battery at the current moment based on the first range and the second range;
and the sending unit is used for sending the target endurance mileage to the terminal equipment so that the terminal equipment displays the target endurance mileage on a display interface.
Optionally, the second obtaining unit is specifically configured to obtain the first electrical energy characterization value by:
acquiring the first electric energy representation value based on the maximum energy value and the state of charge parameter of the battery at the current moment;
the second obtaining unit is specifically configured to obtain a second electrical energy representation value by:
And acquiring the second electric energy representation value based on the maximum capacity value and the state of charge parameter of the battery at the current moment.
Optionally, the second obtaining unit is specifically configured to:
taking the product of the maximum energy value, the state of charge parameter and the state of health parameter of the battery at the current moment as the first electric energy representation value;
the second obtaining unit is specifically configured to:
and taking the product of the maximum capacity value, the state of charge parameter and the state of health parameter of the battery at the current moment as the second electric energy representation value.
Optionally, the state parameters include: the total voltage of the battery at the current moment and the average current parameter of the battery in a preset time period; the preset time period is as follows: a time period of a preset time length is set before the current time.
Optionally, the third obtaining unit is specifically configured to:
taking the product of the first electric energy representation value and the average vehicle speed parameter as a first product value;
taking the product of the total voltage and the average current parameter as a second product value;
based on the ratio of the first product value to the second product value, obtaining a first endurance mileage corresponding to the battery at the current moment;
The third obtaining unit is specifically configured to:
and obtaining a second endurance mileage corresponding to the battery at the current moment based on the product of the second electric energy representation value and the average vehicle speed parameter and the ratio of the average current parameter.
Optionally, the sending unit is further configured to:
acquiring an instantaneous vehicle speed parameter corresponding to the target vehicle at the current moment and an instantaneous current parameter corresponding to the battery at the current moment;
taking the product of the first electric energy representation value and the instantaneous vehicle speed parameter and the ratio of the product of the total voltage and the instantaneous current parameter as a third continuous voyage mileage corresponding to the battery at the current moment;
taking the product of the second electric energy representation value and the instantaneous vehicle speed parameter and the ratio of the instantaneous current state as a fourth endurance mileage corresponding to the battery at the current moment;
predicting a dynamic range corresponding to the battery at the current moment based on the third range and the fourth range;
and sending the dynamic endurance mileage to a terminal device so that the terminal device displays the dynamic endurance mileage on a display interface.
Optionally, the sending unit is further configured to:
If the power consumption function is detected to be started at the current moment and the dynamic endurance mileage is jumped, sending a highlighting instruction to the terminal equipment so that the terminal equipment highlights the jump process on a display interface.
Optionally, the sending unit is further configured to:
acquiring a reference endurance mileage corresponding to the battery at the current moment based on a corresponding relation between a preset state of charge parameter and a endurance mileage predicted value and the state of charge parameter at the current moment; the variation of the reduction of the reference endurance mileage increases with the reduction of the electric quantity of the battery;
and sending the reference range to a terminal device, so that the terminal device can compare and display the reference range with the target range on a display interface.
The embodiment of the application provides a computer program product, which comprises a computer program, and when the computer program is executed by a processor, the method for predicting the endurance mileage is realized.
Optionally, the computer readable storage medium may be implemented as a computer program product, that is, the embodiments of the present application further provide a computer readable storage medium, which includes a computer program, where the computer program when executed by a processor implements a method for predicting a range as any one of the above.
The electronic device provided by the embodiment of the application comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of any one of the prediction methods of the endurance mileage.
The beneficial effects of the application are as follows:
the embodiment of the application provides a prediction method, a prediction device, a vehicle and a computer program product of a endurance mileage, wherein the average speed parameter of a target vehicle and the state parameter of a battery to be detected in the target vehicle are acquired; the method is used for directly predicting the target endurance mileage from the energy consumption source without considering multiple branches of complex energy consumption flow directions, and a plurality of sensors are not needed to be installed to obtain the influence values corresponding to the flow directions of all the branches of the energy consumption, and the influence of errors of the values obtained by the sensors is avoided, so that the prediction process of the target endurance mileage is simpler, the cost is lower, and the obtained prediction result is more accurate.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
fig. 1 is an application scenario schematic diagram of a method for predicting a range according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a prediction apparatus for endurance mileage according to an embodiment of the present application;
fig. 3 is an overall flowchart of a method for executing a range prediction by a processor according to an embodiment of the present application;
FIG. 4 is a graph showing a relationship between a battery temperature and a maximum energy value and a maximum capacity value of the battery, respectively;
fig. 5 is an overall flowchart of another method for predicting a range provided in an embodiment of the present application;
Fig. 6 is a schematic diagram of a hardware composition structure of an electronic device according to an embodiment of the present application;
fig. 7 is a schematic diagram of a hardware composition structure of a computing device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the technical solutions of the present application, but not all embodiments. All other embodiments, which can be made by a person of ordinary skill in the art without any inventive effort, based on the embodiments described in the present application are intended to be within the scope of the technical solutions of the present application.
Some of the concepts involved in the embodiments of the present application are described below.
Average vehicle speed parameter: representing the average speed of the vehicle for a preset period of time, a preset length of time, prior to the current time.
Average current parameter: representing the average current of the battery for a preset period of time of a preset length of time before the current moment.
Change relation: the method is divided into a first change relation and a second change relation, wherein the first change relation represents the change of the current of the battery along with time, and the specific form of the first change relation can be a graph, a table and the like, and the method is not particularly limited; the second variation relationship indicates a variation of the vehicle speed of the target vehicle with time, and may be in a specific form of a graph, a table, or the like, which is not particularly limited in this application.
Range of endurance: representing the mileage that the battery can also travel with the current residual electric quantity; if the target vehicle is an electric vehicle, the endurance mileage is the mileage that the target vehicle can travel at the current moment; if the vehicle is a hybrid vehicle, only the mileage that the battery can still travel with the current residual electric quantity is represented; in the method, the range is divided into a first range, a second range and a target range, wherein the first range is calculated based on a maximum energy value, the second range is calculated based on a maximum capacity value, and the target range is obtained by the first range and the second range.
The preferred embodiments of the present application will be described below with reference to the accompanying drawings of the specification, it being understood that the preferred embodiments described herein are for illustration and explanation only, and are not intended to limit the present application, and embodiments and features of embodiments of the present application may be combined with each other without conflict.
Fig. 1 is a schematic view of an application scenario in an embodiment of the present application. The application scenario diagram includes a vehicle-mounted terminal 110, a prediction device 120 and a terminal device 130.
In the embodiment of the present application, the terminal device 130 includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a desktop computer, an electronic book reader, an intelligent voice interaction device, an intelligent home appliance, and the like; the terminal device may be provided with a client for predicting the target range, where the client may be software (e.g., a browser, target range prediction software, etc.), and may also be a web page, an applet, etc. The in-vehicle terminal 110 and the prediction apparatus 120 are both mounted on the vehicle 10.
It should be noted that, the prediction method of the range in the embodiments of the present application is performed by the prediction device 120. The prediction apparatus 120 acquires an average vehicle speed parameter of a target vehicle, and a state parameter of a battery to be detected in the target vehicle; and a first power characterization value and a second power characterization value of the battery; then, the prediction device 120 obtains a first endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the first electric energy representation value, and obtains a second endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the second electric energy representation value; finally, the prediction device 120 predicts a target range corresponding to the battery at the current time based on the first range and the second range.
After obtaining the target range, the prediction device 120 may directly send the target range to the vehicle-mounted terminal 110 for display, or may send the target range to the terminal device 130, where the terminal device 130 displays the target range.
In an alternative embodiment, the communication between the terminal device 130 and the prediction device 120 may be via a communication network.
In an alternative embodiment, the communication network is a wired network or a wireless network.
It should be noted that, the embodiment shown in fig. 1 is merely an example, and the number of terminal devices is not limited in practice, and is not specifically limited in the embodiment of the present application.
The following describes a method for predicting a range provided in an exemplary embodiment of the present application with reference to the accompanying drawings in combination with the application scenario described above, and it should be noted that the application scenario is only shown for the convenience of understanding the spirit and principles of the present application, and embodiments of the present application are not limited in any way in this respect.
Referring to fig. 2, which is a schematic structural diagram of a range prediction apparatus provided in an embodiment of the present application, where the prediction apparatus 210 includes a processor 211 and a memory 212, and the memory 212 stores a computer program, as shown in fig. 3, is a flowchart for executing range prediction by the processor provided in an embodiment of the present application, and when the computer program is executed by the processor 211, the processor 211 is caused to execute S301-S305:
s301: the processor obtains an average speed parameter of the target vehicle and a state parameter of a battery to be detected in the target vehicle.
The target vehicle may be an electric vehicle or a hybrid vehicle, which is provided with a power source for supplying power, that is, a battery to be detected as mentioned in the present application, and can drive the vehicle by using a motor.
The state parameter is used for describing the internal state and the service condition of the battery; the method mainly comprises the average current parameter of the battery in a preset time period and the total voltage of the battery at the current moment.
The preset time period refers to a period of time within a preset time length before the current time, for example, within Δt time length before the current time; the preset time length can be set according to actual conditions. The processor may obtain the average current parameter and the average vehicle speed parameter by:
the method comprises the steps that a processor obtains a first change relation between current of a battery and time and a second change relation between speed of a target vehicle and time in a preset time period; thereafter, an average current parameter is obtained based on the first variation relationship, and an average vehicle speed parameter is obtained based on the second variation relationship.
Specifically, assuming that the preset time period is within a Δt time period before the current time, the processor may obtain a change curve of the current I with respect to the time t within the Δt time period before the current time, i.e., a first change relation, to calculate a mean value of the current within the Δt time period before the current timeThe specific formula is as follows:
similarly, the processor obtains the variation curve of the vehicle speed V with time t in the time period of deltat before the current moment, namely, the second variation relation, to calculate the average value of the vehicle speed in the time period of deltat before the current moment The specific formula is as follows:
in the above description, t' represents the time at the current time, Δt is a preset time length, and may also be referred to as a time interval, and the value thereof may be set according to the actual situation, for example, Δt may take 10 seconds.
Taking a specific case as an example, assuming that an existing electric vehicle is running, the current time is 52 minutes and 20 seconds at 15 pm, and assuming that the preset time length is 10 seconds, the processor acquires a state of charge parameter, a health state parameter and a total voltage of the battery at the current time, and an average speed parameter of the vehicle and an average current parameter of the battery between 15 minutes and 10 seconds and 15 minutes and 20 seconds.
S302: the processor obtains a first power characterization value and a second power characterization value of the battery.
The first electric energy representation value and the second electric energy representation value can be obtained based on the performance parameters of the battery, the performance parameters of the battery comprise a maximum energy value and a maximum capacity value, the specific values of the two values are affected by the temperature of the battery, and the processor can determine the specific values of the maximum energy value and the maximum capacity value corresponding to the temperature of the battery at the current moment based on the mapping relation between the maximum energy value and the maximum capacity value of the battery and the temperature of the battery.
The maximum energy value is recorded as E max The maximum capacity value is marked as C max As shown in fig. 4, a table diagram is provided for comparing the relationship between the battery temperature and the maximum energy value and the maximum capacity value of the battery, wherein the maximum energy value, the maximum capacity value and the battery temperature Temp respectively show a one-to-one mapping relationship; the specific numerical value of the mapping relation can obtain a relatively accurate result through a capacity test in advance. And then, according to the battery temperature at the current moment, a table look-up method is adopted to obtain specific values of the maximum energy value and the maximum capacity value of the battery at the current temperature.
In an alternative embodiment, the first power characteristic and the second power characteristic are obtained by: acquiring a first electric energy representation value based on the maximum energy value and a state of charge parameter of the battery at the current moment; and acquiring a second electric energy representation value based on the maximum capacity value and the state of charge parameter of the battery at the current moment.
Further, the processor may take a product of the maximum energy value, a state of charge parameter of the battery at the current time, and a state of health parameter of the battery at the current time as the first electrical energy representation value; taking the product of the maximum capacity value, the state of charge parameter of the battery at the current moment and the state of health parameter of the battery at the current moment as a second electric energy representation value, wherein the specific formula is as follows:
First electrical energy characterization value=e max *SOH*S
Second electrical energy characterization value=c max *SOH*SOC
In the above description, SOC is a state of charge parameter at the current time; SOH is the health state parameter at the current moment.
Following the assumption in S301, the processor detects that the current battery temperature is Temp 7 Determining the maximum energy value of the current battery as E according to a relation comparison table of the battery temperature and the maximum energy value and the maximum capacity value of the battery respectively max7 Maximum capacity value C max7 The method comprises the steps of carrying out a first treatment on the surface of the The processor multiplies the maximum energy value, the state of charge parameter of the battery at the current moment and the state of health parameter of the battery at the current moment to obtain a first electric energy representation value; and multiplying the maximum capacity value, the state of charge parameter of the battery at the current moment and the state of health parameter of the battery at the current moment to obtain a second electric energy representation value.
S303: the processor obtains a first endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the first electric energy representation value, and obtains a second endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the second electric energy representation value.
The calculating manner of the first endurance mileage may be: taking the product of the first electric energy characterization value and the average vehicle speed parameter as a first product value; taking the product of the total voltage and the average current parameter as a second product value; and obtaining a first endurance mileage corresponding to the battery at the current moment based on the ratio of the first product value to the second product value.
The maximum energy value is recorded as E maxi The specific value of the battery temperature Temp is Temp i At the time, the corresponding maximum energy value is E maxi The method comprises the steps of carrying out a first treatment on the surface of the The average vehicle speed parameter is recorded asThe average current parameter is recorded as->The state of charge parameter at the current moment is recorded as SOC; the health state parameter at the current moment is recorded as SOH; the total pressure at the current moment is recorded as Ubat; then the first range L E The calculation formula of (2) is as follows:
the calculating manner of the second endurance mileage may be: and obtaining a second endurance mileage corresponding to the current moment of the battery based on the product of the second electric energy representation value and the average vehicle speed parameter and the ratio of the average current parameter.
The maximum capacity value is marked as C maxi The specific value of the battery temperature Temp is Temp i At the time, the corresponding maximum capacity value is C maxi The method comprises the steps of carrying out a first treatment on the surface of the The average vehicle speed parameter is recorded asThe average current parameter is recorded as->The state of charge parameter at the current moment is recorded as SOC; the health state parameter at the current moment is recorded as SOH; then the second range L C The calculation formula of (2) is as follows:
using the assumption in S302, after the processor obtains the first electric energy representation value and the second electric energy representation value, calculating the product of the first electric energy representation value and the average vehicle speed parameter and the ratio of the product of the total voltage and the average current parameter to obtain a first endurance mileage; and calculating the product of the second electric energy representation value and the average vehicle speed parameter and the ratio of the average current state to obtain the second endurance mileage.
S304: the processor predicts a target range corresponding to the current moment of the battery based on the first range and the second range.
S305: and the processor sends the target endurance mileage to the terminal equipment so that the terminal equipment displays the target endurance mileage on a display interface.
If the target vehicle is an electric vehicle, the target endurance mileage corresponding to the battery at the current moment predicted based on the method is also the target endurance mileage which can be used by the target vehicle at the current moment; in the case of a hybrid vehicle, the hybrid vehicle may also rely on the internal combustion engine for driving, so that only the target range corresponding to the current time of the battery is predicted based on the method.
An alternative implementation manner is to take the average value of the first range and the second range as the target range.
The maximum energy value is recorded as E maxi The maximum capacity value is marked as C maxi The specific value of the battery temperature Temp is Temp i At the time, the corresponding maximum energy value is E maxi Maximum capacity value C maxi The method comprises the steps of carrying out a first treatment on the surface of the The average vehicle speed parameter is recorded asThe average current parameter is recorded as->The state of charge parameter at the current moment is recorded as SOC; the health state parameter at the current moment is recorded as SOH; the total pressure at the current moment is recorded as Ubat; the calculation formula of the target endurance mileage L is as follows:
In addition, the first range or the second range can be directly used as the target range.
The SOC, that is, the state of charge parameter, in the calculation process of each endurance mileage is calculated based on the capacity ampere-hour integration method, and the formula is specifically as follows:
wherein SOC is 0 Is the initial electrical quantity value of the battery state of charge; CE is the rated capacity of the battery; i (t) is the charge and discharge current of the battery at the moment t; t is t 1 Is the time of charge and discharge.
When the battery power is reduced, the total voltage of the battery is also reduced, so that the motor still outputs the same power, the vehicle speed is kept unchanged, the battery current is required to be increased according to the power=voltage×current, and the current is gradually increased according to the capacity ampere-hour integration formula, so that the reduction amplitude is larger and larger when the SOC is reduced along with the power. The SOC decreases faster and faster, and the endurance mileage decreases faster and faster, for example, when the electric quantity is sufficient, for example 99% of the electric quantity, and other conditions hardly change, the vehicle travels a distance L during the process of decreasing the electric quantity to 98% a When the electric quantity is insufficient, for example, the electric quantity is 37%, the vehicle runs for a distance L during the process of falling to 36% b L will appear a Is significantly greater than L b This is easily confusing to the driver and may be misinterpreted as a problem in calculating the range.
In the calculation method proposed in the present application, L can be seen according to the formula E In the calculation process of (2), the total battery voltage Ubat also can be reduced along with the reduction of electric quantity, so that the influence of rapid reduction of the continuous voyage mileage caused by rapid reduction of the SOC in a part of molecules can be counteracted, the continuous voyage mileage can be uniformly reduced along with time, but not along with time development, and the reduction amplitude of the continuous voyage mileage is also larger and larger. Under the method provided by the application, assuming that the rest conditions are the same, the vehicle travels a distance L in the process of reducing the electric quantity from 99% to 98% c While the vehicle travels a distance L during the period when the electric quantity is reduced from 37% to 36% d Then there is L c ≈L d And L is c ＜L a ，L d ＞L b 。
In the method for predicting the endurance mileage, the average speed parameter and the average current parameter are needed, in addition, the instantaneous speed parameter corresponding to the current moment of the target vehicle and the instantaneous current parameter corresponding to the current moment of the battery can be adopted to obtain the dynamic endurance mileage, and the dynamic endurance mileage is also sent to the terminal equipment, so that the terminal equipment displays the dynamic endurance mileage on the display interface, or displays the target endurance mileage and the dynamic endurance mileage at the same time.
The dynamic endurance mileage is obtained by the following steps: the processor takes the product of the first electric energy representation value and the instantaneous vehicle speed parameter and the ratio of the product of the total voltage and the instantaneous current parameter as a third continuous voyage mileage corresponding to the current moment of the battery; taking the product of the second electric energy representation value and the instantaneous vehicle speed parameter and the ratio of the instantaneous current state as a fourth endurance mileage corresponding to the battery at the current moment; finally, the processor predicts the dynamic range corresponding to the current time of the battery based on the third range and the fourth range, and specifically may take the average value of the third range and the fourth range as the dynamic range, or adopt a weighted summation mode.
The dynamic endurance mileage adopts instantaneous values of the speed and the current, so when the speed of the target vehicle is fluctuated severely, or when the current of a battery is unstable and even fluctuated severely due to the starting of a certain power consumption function in the vehicle, the dynamic endurance mileage can also change greatly along with the current, and therefore, the processor can send a highlighting instruction to the terminal equipment when the power consumption function is detected to be started at the current moment and the dynamic endurance mileage jumps, so that the terminal equipment highlights the jump process on a display interface.
In addition, the corresponding relation between the state of charge parameter and the predicted range value can be preset, the predicted range value is obtained only according to the state of charge parameter, and the processor can obtain the reference range corresponding to the current moment of the battery according to the state of charge parameter at the current moment; and the reference range is also sent to the terminal equipment, so that the terminal equipment can compare and display the reference range with the target range on the display interface.
In the description of the above SOC calculation formula, it may be known that the state of charge parameter SOC does not decrease uniformly, but decreases faster and faster, and the estimated range value obtained only according to the SOC also decreases faster and faster, that is, the variation of the reference range decrease increases with the decrease of the electric quantity of the battery.
In the present application, it is specified that the vehicle speed is positive, that is, greater than 0, while the vehicle is in forward direction, negative, that is, less than 0, while the vehicle is in reverse direction, and 0 while the vehicle is in stop; the current in discharging is positive, and the current in charging is negative; further, the charging includes parking gun charging and feedback charging when an accelerator pedal is released or a brake pedal is stepped on in driving. When the target vehicle is in a parking gun charging state, the processor does not predict the target endurance mileage because the vehicle speed is 0; in the state of non-parking gun insertion charging, if one parameter of the average vehicle speed parameter and the average current parameter corresponding to the time period within the preset time period is smaller than or equal to 0 or both parameters are smaller than or equal to 0 before the current moment, the state parameters of the target vehicle are unstable and even fluctuate severely under the state, so that the target range at the current moment can follow the last prediction result, namely the value of the last predicted target range, and when the average vehicle speed parameter and the average current parameter are larger than 0, the processor predicts the target range based on the method.
Therefore, compared with a mode of updating the range in real time under any condition, the target range in the method can be predicted only under the condition that the target vehicle is stably driven, and the predicted result is more accurate; compared with a mode of periodically updating the endurance mileage according to a preset period (for example, predicting once in 5 minutes), the predicted result of the method is more timely.
Further, the above-described calculation process may be performed by a processor mounted on the vehicle, for example, by a battery management system. The predicted target endurance mileage can be directly displayed on the vehicle-mounted terminal, and the target endurance mileage can be sent to other terminal equipment through a communication network and displayed on the other terminal equipment, and the application is not particularly limited.
And (3) continuing the assumption in S303, after the processor acquires the first and second range, the processor acquires the average value of the first and second range, acquires the predicted target range, and transmits the target range to the terminal equipment, and in addition, the processor can acquire the dynamic range and the reference range and transmit the dynamic range and the reference range to the terminal equipment for comparison and display.
In summary, in the prior art, the method for predicting the endurance mileage by adopting NEDC is to calculate the angle of the energy consumption flow direction of the whole vehicle, for example, the energy consumption required for resisting wind resistance, the energy consumption required for an air conditioner, the load, the vehicle speed and the like have influence on the energy consumption; however, as the whole vehicle energy consumption flows to more branches, the data acquisition of factor data influencing the energy consumption of each branch is generally difficult, a large number of various sensors are needed to complete the data acquisition, and the measured result error is larger; and because of too many factors influencing the energy consumption, the method always considers incomplete influencing factors, for example, road conditions, braking feedback strategies and the like are not considered; and finally, a larger error exists between a calculation result and an actual driving mileage which can be supported by the actual electric quantity, the calculation result is always 15 to 30 percent larger than the actual driving mileage, and the calculation result has little significance for guiding the journey planning of drivers and passengers.
The method and the device calculate from the whole vehicle energy consumption source, combine battery energy, battery capacity, battery state of charge, total battery voltage, battery current, battery temperature and battery life, calculate the endurance mileage of the battery in real time, avoid the influence of each influence factor test error on the endurance mileage calculation result in each energy branch, and do not need to arrange various data sensors, save the cost of the whole vehicle, simultaneously, the prediction result of the target endurance mileage is more accurate, provide references for the travel planning of drivers in real time, and promote the driving experience.
Based on the above process, as shown in fig. 5, an overall flowchart of another method for predicting a range provided in an embodiment of the present application is shown, where the server specifically executes the following steps:
step 501: the processor obtains an average speed parameter of the target vehicle and a state parameter of a battery to be detected in the target vehicle.
The state parameters comprise the total voltage of the battery at the current moment and the average current parameter of the battery in a preset time period.
Step 502: the processor obtains the temperature of the current battery.
Step 503: the processor determines a corresponding target performance parameter based on the temperature of the current battery.
Wherein the target performance parameter includes a maximum energy value and a maximum capacity value.
Step 504: the processor takes the product of the maximum energy value, the state of charge parameter and the state of health parameter of the battery at the current moment as a first electric energy representation value.
Step 505: the processor takes the product of the maximum capacity value, the state of charge parameter and the state of health parameter of the battery at the current moment as a second electric energy representation value.
Step 506: the processor obtains the product of the first electric energy representation value and the average vehicle speed parameter and the ratio of the product of the total voltage and the average current parameter to obtain the first endurance mileage.
Step 507: the processor obtains the product of the second electric energy representation value and the average vehicle speed parameter and the ratio of the average current state to obtain the second endurance mileage.
Step 508: and the processor takes the average value of the first continuous voyage mileage and the second continuous voyage mileage as the target continuous voyage mileage of the current moment of the battery.
In the above description, the first range obtained in step 506 may also be directly used as the target range, and the second range obtained in step 507 may also be directly used as the target range.
Having described the apparatus and method for predicting a range of an exemplary embodiment of the present application, next, an electronic apparatus according to another exemplary embodiment of the present application is described.
Those skilled in the art will appreciate that the various aspects of the present application may be implemented as a system, method, or program product. Accordingly, aspects of the present application may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.
The embodiment of the application also provides electronic equipment based on the same inventive concept as the embodiment of the method. In one embodiment, the electronic device may be the predictive device 120 shown in FIG. 1. In this embodiment, the electronic device may be configured as shown in fig. 6, including a memory 601, a communication module 603, and one or more processors 602.
A memory 601 for storing a computer program for execution by the processor 602. The memory 601 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, programs required for running an instant messaging function, and the like; the storage data area can store various instant messaging information, operation instruction sets and the like.
The memory 601 may be a volatile memory (RAM) such as a random-access memory (RAM); the memory 601 may also be a nonvolatile memory (non-volatile memory), such as a read-only memory (rom), a flash memory (flash memory), a hard disk (HDD) or a Solid State Drive (SSD); or memory 601, is any other medium capable of carrying or storing a desired computer program in the form of instructions or data structures and capable of being accessed by a computer, but is not limited to such. The memory 601 may be a combination of the above memories.
The processor 602 may include one or more central processing units (central processing unit, CPU) or digital processing units, etc. And a processor 602, configured to implement the method for predicting the target range when calling the computer program stored in the memory 601.
The communication module 603 is used for communicating with terminal devices and other servers.
The specific connection medium between the memory 601, the communication module 603, and the processor 602 is not limited in the embodiment of the present application. The embodiment of the present application is shown in fig. 6, where the memory 601 and the processor 602 are connected by a bus 604, and the bus 604 is shown in fig. 6 with a bold line, and the connection between other components is merely illustrative, and not limited to the above. The bus 604 may be divided into an address bus, a data bus, a control bus, and the like. For ease of description, only one thick line is depicted in fig. 6, but only one bus or one type of bus is not depicted.
The memory 601 stores a computer storage medium, and the computer storage medium stores computer executable instructions for implementing the method for predicting the target range according to the embodiments of the present application. The processor 602 is configured to execute the above-described method for predicting the target range, as shown in fig. 3.
A computing device 700 according to such an embodiment of the present application is described below with reference to fig. 7. The computing device 700 of fig. 7 is only one example and should not be taken as limiting the functionality and scope of use of embodiments of the present application.
As shown in fig. 7, computing device 700 is in the form of a general purpose computing device. Components of computing device 700 may include, but are not limited to: the at least one processing unit 701, the at least one memory unit 702, and a bus 703 that connects the different system components (including the memory unit 702 and the processing unit 701).
Bus 703 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a processor, and a local bus using any of a variety of bus architectures.
The storage unit 702 may include readable media in the form of volatile memory, such as Random Access Memory (RAM) 721 and/or cache memory 722, and may further include Read Only Memory (ROM) 723.
The storage unit 702 may also include a program/utility 725 having a set (at least one) of program modules 724, such program modules 724 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
The computing device 700 may also communicate with one or more external devices 704 (e.g., keyboard, pointing device, etc.), one or more devices that enable a user to interact with the computing device 700, and/or any devices (e.g., routers, modems, etc.) that enable the computing device 700 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 705. Moreover, the computing device 700 may also communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through the network adapter 706. As shown in fig. 7, the network adapter 706 communicates with other modules for the computing device 700 over the bus 703. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with computing device 700, including, but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
Embodiments of the present application also provide a computer program product, where the methods of the present application may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described herein are performed in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, a network device, a user device, a core network device, an OAM, or other programmable apparatus.
The computer readable storage medium may be implemented as a computer program product, that is, the embodiments of the present application further provide a computer readable storage medium, which includes a computer program, where the computer program when executed by a processor implements a method for integrating whole vehicle upgrade software as any one of the above.
The computer program or instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer program or instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired or wireless means. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that integrates one or more available media. The usable medium may be a magnetic medium, e.g., floppy disk, hard disk, tape; but also optical media such as digital video discs; but also semiconductor media such as solid state disks. The computer readable storage medium may be volatile or nonvolatile storage medium, or may include both volatile and nonvolatile types of storage medium.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.

Claims (12)

1. The method for predicting the endurance mileage is characterized by comprising the following steps:
acquiring an average speed parameter of a target vehicle and a state parameter of a battery to be detected in the target vehicle; wherein the state parameter is used for describing the internal state and the service condition of the battery;
acquiring a first electric energy representation value and a second electric energy representation value of the battery;
obtaining a first endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the first electric energy representation value, and obtaining a second endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the second electric energy representation value;
predicting a target range corresponding to the battery at the current moment based on the first range and the second range;
and sending the target endurance mileage to a terminal device, so that the terminal device displays the target endurance mileage on a display interface.
2. The method of claim 1, wherein the first power characterization value is obtained by:
acquiring the first electric energy representation value based on the maximum energy value and the state of charge parameter of the battery at the current moment;
The second electric energy characterization value is obtained by the following method:
and acquiring the second electric energy representation value based on the maximum capacity value and the state of charge parameter of the battery at the current moment.
3. The method of claim 2, wherein the obtaining the first power characterization value based on a maximum energy value and a state of charge parameter of the battery at a current time comprises:
taking the product of the maximum energy value, the state of charge parameter and the state of health parameter of the battery at the current moment as the first electric energy representation value;
the obtaining the second electric energy representation value based on the maximum capacity value and the state of charge parameter of the battery at the current moment includes:
and taking the product of the maximum capacity value, the state of charge parameter and the state of health parameter of the battery at the current moment as the second electric energy representation value.
4. The method of claim 1, wherein the status parameters comprise: the total voltage of the battery at the current moment and the average current parameter of the battery in a preset time period; the preset time period is as follows: a time period of a preset time length is set before the current time.
5. The method of claim 4, wherein the obtaining a first range for the battery at the current time based on the average vehicle speed parameter, the state parameter, and the first power characterization value comprises:
taking the product of the first electric energy representation value and the average vehicle speed parameter as a first product value;
taking the product of the total voltage and the average current parameter as a second product value;
based on the ratio of the first product value to the second product value, obtaining a first endurance mileage corresponding to the battery at the current moment;
the obtaining, based on the average vehicle speed parameter, the state parameter and the second electric energy representation value, a second endurance mileage corresponding to the battery at the current moment includes:
and obtaining a second endurance mileage corresponding to the battery at the current moment based on the product of the second electric energy representation value and the average vehicle speed parameter and the ratio of the average current parameter.
6. The method of claim 5, wherein the method further comprises:
acquiring an instantaneous vehicle speed parameter corresponding to the target vehicle at the current moment and an instantaneous current parameter corresponding to the battery at the current moment;
Taking the product of the first electric energy representation value and the instantaneous vehicle speed parameter and the ratio of the product of the total voltage and the instantaneous current parameter as a third continuous voyage mileage corresponding to the battery at the current moment;
taking the product of the second electric energy representation value and the instantaneous vehicle speed parameter and the ratio of the instantaneous current state as a fourth endurance mileage corresponding to the battery at the current moment;
predicting a dynamic range corresponding to the battery at the current moment based on the third range and the fourth range;
and sending the dynamic endurance mileage to a terminal device so that the terminal device displays the dynamic endurance mileage on a display interface.
7. The method of claim 6, wherein the method further comprises:
if the power consumption function is detected to be started at the current moment and the dynamic endurance mileage is jumped, sending a highlighting instruction to the terminal equipment so that the terminal equipment highlights the jump process on a display interface.
8. The method of any one of claims 1-7, further comprising:
acquiring a reference endurance mileage corresponding to the battery at the current moment based on a corresponding relation between a preset state of charge parameter and a endurance mileage predicted value and the state of charge parameter at the current moment; the variation of the reduction of the reference endurance mileage increases with the reduction of the electric quantity of the battery;
And sending the reference range to a terminal device, so that the terminal device can compare and display the reference range with the target range on a display interface.
9. The utility model provides a prediction device of continuation of journey mileage which characterized in that includes:
a first acquisition unit configured to acquire an average vehicle speed parameter of a target vehicle and a state parameter of a battery to be detected in the target vehicle; wherein the state parameter is used for describing the internal state and the service condition of the battery;
the second acquisition unit is used for acquiring a first electric energy representation value and a second electric energy representation value of the battery;
the third obtaining unit is configured to obtain a first endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the first electric energy representation value, and obtain a second endurance mileage corresponding to the battery at the current moment based on the average vehicle speed parameter, the state parameter and the second electric energy representation value;
the prediction unit is used for predicting a target range corresponding to the battery at the current moment based on the first range and the second range;
And the sending unit is used for sending the target endurance mileage to the terminal equipment so that the terminal equipment displays the target endurance mileage on a display interface.
10. An electronic device comprising a processor and a memory, wherein the memory stores a computer program which, when executed by the processor, causes the processor to perform the steps of the method of any of claims 1 to 8.
11. A vehicle characterized in that it comprises an electronic device that performs the prediction method of the range of any one of claims 1 to 8.
12. A computer program product comprising a computer program, characterized in that the steps of the method according to any one of claims 1 to 8 are implemented when said computer program is executed by a device.
CN202311567780.3A 2023-11-21 2023-11-21 Method and device for predicting endurance mileage, vehicle and computer program product Pending CN117382424A (en)

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