CN117574694A - Method for shortening driving range and simulating and analyzing energy consumption of pure electric vehicle - Google Patents
Method for shortening driving range and simulating and analyzing energy consumption of pure electric vehicle Download PDFInfo
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Abstract
The invention provides a method for simulating and analyzing the driving range and the energy consumption of a pure electric vehicle by shortening the method, which relates to the technical field of the energy consumption test of the electric vehicle and comprises the following steps: and constructing a driving range simulation model of the electric automobile, and calculating a first running time required by the battery electric quantity to be reduced to the set battery electric quantity in combination with the set battery electric quantity. Setting the first operation time as the total operation time of the shortened method DS1 and CSSM working conditions; and then detecting the energy consumption and the driving range of each working condition of the shortening method. And finally, calculating the driving range and hundred kilometers of energy consumption of the electric automobile according to the driving range and the energy consumption. The method for calculating the first running time by using the set battery electric quantity and controlling the shortened method working condition running time not only can replace test verification compared with a conventional working condition method, but also occupies about 50% less simulation resources compared with the conventional working condition method. Because the production real vehicle test is not needed at all, the vehicle research and development period can be effectively reduced.
Description
Technical Field
The invention relates to the technical field of electric vehicle energy consumption testing, in particular to a method for shortening driving range and simulating and analyzing energy consumption of a pure electric vehicle.
Background
Along with the continuous improvement of the driving range of the electric automobile, the shortened driving range test also becomes the most commonly used test method in the electric automobile type authentication and product development process. At present, a conventional working condition method is adopted for virtual simulation of the driving range in the product development period, so that the test working condition cannot be completely simulated, and the error of the test result is larger.
When a few shortening methods are used for carrying out virtual simulation test on the energy consumption and the driving mileage of the electric automobile, the relation of the change of the battery power with time is difficult to combine; for example, a condition is not completed, and the battery power is about to be consumed. It is difficult to allocate the running time and the battery power SOC of the four parts of the first cycle condition DS1, the first constant speed condition CSSM, the second cycle condition DS2, and the second constant speed condition CSSE according to the shortening method, so as to achieve the best test effect. And further, repeated simulation is needed for many times, more simulation resources are occupied, and the research and development period is prolonged.
Disclosure of Invention
In view of the above-mentioned drawbacks or shortcomings in the prior art, it is desirable to provide a method for shortening the driving range and simulating and analyzing the energy consumption of a pure electric vehicle.
The invention provides a method for simulating and analyzing the driving mileage and energy consumption of a pure electric vehicle by a shortening method, which comprises the following steps:
constructing a driving range simulation model of the electric automobile;
acquiring a set battery electric quantity;
calculating the time required for the battery electric quantity to be reduced to the set battery electric quantity according to the set battery electric quantity, and obtaining a first running time;
setting the first operation time as the total operation time of the shortened method DS1 and CSSM working conditions;
DS1, CSSM, DS2 and CSSE working conditions of a shortening method are carried out on the driving range simulation model;
in the process of detecting DS1 and DS2 working conditions, the driving mileage simulation model simulates driving mileage and energy consumption obtained by the electric automobile;
and calculating the driving range and hundred kilometers of energy consumption of the electric automobile according to the driving range and the energy consumption in the DS1 and DS2 working conditions.
According to the technical scheme provided by the invention, the process of calculating the time required for the battery electric quantity to be reduced to the set battery electric quantity according to the set battery electric quantity and obtaining the first running time comprises the following steps:
DS1 and CSSM working conditions of a shortening method are carried out on the driving range simulation model;
counting the battery electric quantity at each moment in the DS1 and CSSM working conditions to obtain a time-varying curve of the battery electric quantity;
substituting the set battery electric quantity into the time-varying curve of the battery electric quantity, and calculating the time required for the battery electric quantity to be reduced to the set battery electric quantity to obtain the first running time.
According to the technical scheme provided by the invention, the mode of setting the first operation time to shorten the total operation time of the DS1 and CSSM working conditions is as follows:
setting the time at which the shortening method starts to be zero;
calculating the starting operation time of the DS2 working condition according to the zero time and the first operation time to obtain a first operation time;
starting from the moment of starting the shortening method to the first operation moment, carrying out DS1 and CSSM working conditions;
and from the first operation time, DS2 working conditions and CSSE working conditions are sequentially carried out.
According to the technical scheme provided by the invention, the DS1 comprises: a first circulation driving condition and a second circulation driving condition; the DS2 includes: a third cycle running condition and a fourth cycle running condition;
the driving mileage during DS1 operating mode includes: the driving range simulation model simulates a first driving range obtained by the electric automobile in the first cycle driving condition process; a second driving range during a second cycle driving condition;
the energy consumption during DS1 operation includes: first energy consumption during a first cycle running condition; the second energy consumption in the second cycle driving working condition process;
the driving mileage during DS2 operating mode includes: a third driving range during a third cycle driving condition; a fourth driving range during a fourth cycle driving condition;
the energy consumption during DS2 operation includes: third energy consumption during a third cycle driving condition; and fourth energy consumption during fourth cycle driving conditions.
According to the technical scheme provided by the invention, hundred kilometer energy consumption of the electric automobile is calculated by a formula I;
formula one;
wherein EC_100 is hundred kilometers of energy consumption, E_DC1 is first energy consumption, E_DC2 is second energy consumption, E_DC3 is third energy consumption, E_DC4 is fourth energy consumption, S 1 、S 2 、S 3 、S 4 The first driving distance, the second driving distance, the third driving distance, the fourth driving distance and the E_REESS are the total energy consumption of the whole working condition of the shortening method respectively.
According to the technical scheme provided by the invention, the driving range of the electric automobile is calculated by a formula II;
a second formula;
wherein BER is the driving range, EC_100 is hundred kilometers of energy consumption, and E_REESS is the total energy consumption of the whole working condition of the shortening method.
The invention has the beneficial effects that:
after the driving range simulation model of the electric automobile is built, the set battery electric quantity is combined, and the time required for the battery electric quantity to be reduced to the set battery electric quantity is calculated, so that the first running time is obtained. And setting the first operation time as the total operation time of the shortening method DS1 and CSSM working conditions, and then carrying out the whole working condition process of the shortening method. And in the process, detecting the energy consumption of each working condition and the driving mileage virtually simulated by the driving mileage simulation model. And finally, calculating the driving range and hundred kilometers of energy consumption of the electric automobile according to the driving range and the energy consumption. The method can realize the simulation analysis of the driving mileage of the whole vehicle by shortening the method, obtain the energy consumption performance close to the test working condition in the early stage of the research and development of the whole vehicle, and provide a basis for the power matching and the part model selection of the whole vehicle energy management. The method for calculating the first running time by using the set battery electric quantity and controlling the shortened method working condition running time not only can replace test verification compared with a conventional working condition method, but also occupies about 50% less simulation resources compared with the conventional working condition method. Because the production real vehicle test is not needed at all, the vehicle research and development period can be effectively reduced.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the accompanying drawings in which:
FIG. 1 is a schematic flow chart of a method for simulating and analyzing the driving range and the energy consumption of a pure electric vehicle by shortening the method;
FIG. 2 is a schematic diagram of a working condition operation flow;
FIG. 3 is a schematic diagram of a shortened process operating mode model;
FIG. 4 is a shortened data processing model;
FIG. 5 is a schematic view of a range simulation model;
1. a signal lumped model; 2. a switching module; 3. DS1 and CSSM operating mode; 4. CSSM working condition ending judgment conditions; 5. DS2 and CSSE conditions; 6. a clock model; 7. a data processing unit; 8. an energy consumption calculation module; 9. a low voltage load; 10. DC/DC; 11. a battery model; 12. a motor model; 13. a speed reducer; 14. a VCU controller; 15. a BMS controller; 16. road surface environment; 17. a tire model; 18. a brake model; 19. a cockpit; 20. a working condition road spectrum model; 21. a driver model; 22. a whole vehicle model; 23. a logic judgment module; 24. a three-electric system; 25. shortening a working condition strategy; 26. a low voltage load module; 27. a delay module; 28. a gain module; 29. and the signal extraction and formula editing module.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the invention are shown in the drawings.
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
Referring to fig. 1 and 2, the present invention provides a method for simulating and analyzing the driving range and energy consumption of a pure electric vehicle by shortening the driving range, which comprises the following steps:
s1: constructing a driving range simulation model of the electric automobile;
s2: acquiring a set battery electric quantity;
s3: calculating the time required for the battery electric quantity to be reduced to the set battery electric quantity according to the set battery electric quantity, and obtaining a first running time;
s4: setting the first operation time as the total operation time of the shortened method DS1 and CSSM working conditions;
s5: DS1, CSSM, DS2 and CSSE working conditions of a shortening method are carried out on the driving range simulation model;
s6: in the process of detecting DS1 and DS2 working conditions, the driving mileage simulation model simulates driving mileage and energy consumption obtained by the electric automobile;
s7: and calculating the driving range and hundred kilometers of energy consumption of the electric automobile according to the driving range and the energy consumption in the DS1 and DS2 working conditions.
In some embodiments, constructing a range simulation model of an electric vehicle in a modelica language includes: the vehicle model 22, the battery model 11, the motor model 12, the VCU controller 14 (vehicle controller Vehicle control unit), the BMS controller 15 (battery control system Battery Management System), the DC/DC 10 (direct current to direct current converter), the low voltage load 9, the driver model 21, the data processing unit 7, the energy consumption calculation module 8, the tire model 17, the brake model 18, the decelerator 13, the road surface environment 16, the cockpit 19, the operating condition road spectrum model 20.
And further construct subsystems of the whole vehicle model, including a whole vehicle module (vehicle body, tires, brakes, etc.), a three-electric system 24 (motor, battery, controller thereof, etc.), a low-voltage load module 26 (load model, DC/DC, etc.), a driver model 21, a signal lumped model 1, and a shortening method working condition strategy 25 (driver, passenger compartment, working condition model, control strategy, etc.).
Specifically, the flow of the simulation includes: firstly, collecting real-time signals of a driving range simulation model through a signal lumped model 1, and processing data required for shortening the driving range calculation through a data processing unit, wherein the data comprise driving range and energy consumption. And then the energy consumption of each stage is calculated by an energy consumption calculation module, and then the driving mileage and hundred kilometers energy consumption of the whole vehicle shortening method are calculated by a formula I and a formula II.
Specifically, the whole vehicle model: for setting the precursor/the postdriver/the four-driver: the whole vehicle basic data such as wheelbase, axle load, sliding resistance coefficient (physical parameter resistance) and the like are used for calculating the whole vehicle resistance.
Cell model: the battery is defined by combining serial and parallel numbers, so that the whole capacity, open-loop electromotive force, internal resistance and the like of the battery are synthesized.
And (3) a motor model: the power generation and electric drive integrated model can define the energy conversion efficiency under different working modes under different voltages; the external characteristic curves for different voltages and different operation modes can be defined.
VCU controller: the general controller model can set main control strategies of a front-drive/rear-drive/four-drive vehicle type and mainly comprises the following steps: electric drive, electric brake, start anti-slip control, etc.
BMS controller: the input and output of the front-drive vehicle type battery can be controlled by current or power.
DC/DC: a converter model for step-up/step-down can simulate the efficiency loss of a voltage-change process.
Low voltage load: for modeling low voltage accessory power consumption.
Driver model: the main control logic is PI control, and parameters such as initial accelerator pedal position, expected deceleration and the like can be set.
A data processing unit: and processing the simulation output parameters of the whole vehicle, calculating and shortening the driving range and the like.
Tire model: the tire model is used for setting radius, rotational inertia, friction coefficient and the like, and calculating the slip ratio of the whole vehicle.
Brake model: the method is used for setting relevant performance parameters of the brake and is used for braking the whole vehicle.
A speed reducer: a speed ratio and transmission efficiency retarder model may be defined.
Road surface environment: the road surface information model is used for setting road surface adhesion coefficient, gravitational acceleration and the like.
And (3) a cockpit: the pedal signal is converted into an input signal that drives the corresponding working member.
Working condition road spectrum model: and a circulation working condition file defined by time-vehicle speed is input, and working condition simulation such as NEDC, CLTC, user definition and the like can be performed.
In some embodiments, the minimum electric quantity represents the minimum electric quantity of the battery pack capable of providing power for the vehicle, and needs to be set according to the actual situation of the battery pack; for example, 10% may be set. The electric quantity of the battery is set according to the experimental requirement, and the experimenter inputs the electric quantity into the testing system.
Specifically, the method for calculating the first running time by using the set battery electric quantity and controlling the shortened method working condition running time is not required to perform energy consumption test on the actual production vehicle compared with the conventional working condition method, so that the method can replace test verification, and occupies about 50% less simulation resources compared with the conventional working condition method. Because the production real vehicle test is not needed at all, the vehicle research and development period can be effectively reduced.
Further, calculating, according to the set battery power, a time required for the battery power to be reduced to the set battery power, and obtaining a first running time includes:
DS1 and CSSM working conditions of a shortening method are carried out on the driving range simulation model;
counting the battery electric quantity at each moment in the DS1 and CSSM working conditions to obtain a time-varying curve of the battery electric quantity;
substituting the set battery electric quantity into the time-varying curve of the battery electric quantity, and calculating the time required for the battery electric quantity to be reduced to the set battery electric quantity to obtain the first running time.
Specifically, CSSM and CSSE represent a first constant-speed running condition and a second constant-speed running condition, respectively.
In this embodiment, from the full battery pack, the DS1 and CSSM conditions of the shortening method are detected in real time, and a curve of the change of the battery power SOC with time is generated until the battery power SOC is reduced to the minimum power for the normal operation of the vehicle. The first run time indicates the time required for the battery to drop to the set battery charge when the battery begins at full charge and the vehicle is operating in DS1 and CSSM.
In the subsequent test process, a retest or calculation process can be omitted, and the effects of reducing test items and shortening research and development time can be achieved.
In the DS1 and CSSM working conditions, real-time vehicle speed virtually generated by the driving range simulation model is monitored, the real-time vehicle speed is compared with a value corresponding to running time in a target vehicle speed curve of an experimental design, a pedal signal is generated after the processing of a driver model, the pedal signal is processed by a VCU controller, driving motor driving or energy recovery, brake deceleration and the like are further controlled, and driving force and braking force are processed by a whole vehicle balance equation of the whole vehicle module of FIG. 2 to drive acceleration or deceleration of the whole vehicle. The method can automatically adjust the difference between the real-time simulated vehicle speed and the target vehicle speed, so that the two speeds are kept consistent as much as possible.
Further, the method for setting the first operation time to shorten the total operation time of the method DS1 and CSSM working conditions is as follows:
setting the time at which the shortening method starts to be zero;
calculating the starting operation time of the DS2 working condition according to the zero time and the first operation time to obtain a first operation time;
starting from the moment of starting the shortening method to the first operation moment, carrying out DS1 and CSSM working conditions;
and from the first operation time, DS2 working conditions and CSSE working conditions are sequentially carried out.
In some embodiments, the first operation time is obtained by calculating the set battery power, and then the operation time of the subsequent shortening method DS1 and CSSM working conditions is set according to the first operation time, so that the battery power can be obtained in real time because the corresponding relationship between the battery power SOC and the time is consistent. And then, from the first operation moment, sequentially carrying out DS2 and CSSE working conditions, and finally, when the battery power SOC reaches the minimum power, indicating that the whole process is completed.
Further, the DS1 includes: a first circulation driving condition and a second circulation driving condition; the DS2 includes: a third cycle running condition and a fourth cycle running condition;
the driving mileage during DS1 operating mode includes: the driving range simulation model simulates a first driving range obtained by the electric automobile in the first cycle driving condition process; a second driving range during a second cycle driving condition;
the energy consumption during DS1 operation includes: first energy consumption during a first cycle running condition; the second energy consumption in the second cycle driving working condition process;
the driving mileage during DS2 operating mode includes: a third driving range during a third cycle driving condition; a fourth driving range during a fourth cycle driving condition;
the energy consumption during DS2 operation includes: third energy consumption during a third cycle driving condition; and fourth energy consumption during fourth cycle driving conditions.
Specifically, the driving mileage includes: the first driving distance, the second driving distance, the third driving distance and the fourth driving distance. The energy consumption includes: the first energy consumption, the second energy consumption, the third energy consumption and the fourth energy consumption, and the total energy consumption E_REESS of the whole working condition of the shortening method. The specific numerical values of the parameters are all monitored by simulation software in the whole working condition process of the shortening method, and are output and displayed after the working condition is finished.
Specifically, the cycle driving conditions mainly include driving conditions such as starting, accelerating, constant speed, decelerating, turning, ascending and descending, stopping and the like according to the movement form of the automobile. According to the control mode of a driver, the working conditions of gear shifting, sliding (gear-off sliding, neutral gear sliding, acceleration sliding and parking sliding), braking (emergency braking, speed regulation braking and braking), accelerator speed regulation, steering, reversing and the like are mainly adopted. According to the load conditions, the working conditions of empty load, full load (equal to rated load), overload (exceeding rated load) and the like are mainly adopted.
Because the DS1 and CSSM working conditions are only used for constructing the change relation of the battery electric quantity SOC along with time, the driving mileage and energy consumption under the whole working conditions of the latter part shortening method are only counted for calculation in the embodiment.
Further, hundred kilometer energy consumption of the electric automobile is calculated by a formula I;
formula one;
wherein EC_100 is hundred kilometers of energy consumption, E_DC1 is first energy consumption, E_DC2 is second energy consumption, E_DC3 is third energy consumption, E_DC4 is fourth energy consumption, S 1 、S 2 、S 3 、S 4 The first driving distance, the second driving distance, the third driving distance, the fourth driving distance and the E_REESS are the total energy consumption of the whole working condition of the shortening method respectively.
Further, the driving range of the electric automobile is calculated by a formula II;
a second formula;
wherein BER is the driving range, EC_100 is hundred kilometers of energy consumption, and E_REESS is the total energy consumption of the whole working condition of the shortening method.
Specifically, in formula one, the x represents multiplication.
The driving mileage includes: the first driving distance, the second driving distance, the third driving distance and the fourth driving distance.
The energy consumption includes: the first energy consumption, the second energy consumption, the third energy consumption and the fourth energy consumption, and the total energy consumption E_REESS of the whole working condition of the shortening method.
Hundred kilometers of energy consumption is calculated through the formula I, and then the energy consumption is substituted into the formula II to obtain the driving range through calculation.
Fig. 3 includes: the signal lumped model 1, the switching module 2, the working condition for switching simulation cycle, DS1 and CSSM working condition 3, represent and carry out DS2 and CSSE working condition, CSSM working condition end judging condition 4 is used for judging whether the running time reaches the condition of CSSM working condition end, and then carries out DS2 and CSSE working condition 5, the clock model 6 is used for setting the running time of the whole shortening method, the delay module 27, the gain module 28 and the signal extraction and formula editing module 29 are used for defining the initial vehicle speed.
Fig. 4 includes: a signal lumped model 1, a data processing unit 7 and an energy consumption calculation module 8.
In fig. 5, the logic determination module 23 is used to control the on or off of the low voltage load 9.
The above description is only illustrative of the preferred embodiments of the present invention and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the invention referred to in the present invention is not limited to the specific combinations of the technical features described above, but also covers other technical features formed by any combination of the technical features described above or their equivalents without departing from the inventive concept. Such as the above-mentioned features and the technical features disclosed in the present invention (but not limited to) having similar functions are replaced with each other.
Claims (6)
1. A method for simulating and analyzing the driving range and the energy consumption of a pure electric vehicle by a shortening method is characterized by comprising the following steps:
constructing a driving range simulation model of the electric automobile;
acquiring a set battery electric quantity;
calculating the time required for the battery electric quantity to be reduced to the set battery electric quantity according to the set battery electric quantity, and obtaining a first running time;
setting the first operation time as the total operation time of the shortened method DS1 and CSSM working conditions;
DS1, CSSM, DS2 and CSSE working conditions of a shortening method are carried out on the driving range simulation model;
in the process of detecting DS1 and DS2 working conditions, the driving mileage simulation model simulates driving mileage and energy consumption obtained by the electric automobile;
and calculating the driving range and hundred kilometers of energy consumption of the electric automobile according to the driving range and the energy consumption in the DS1 and DS2 working conditions.
2. The method for simulating and analyzing the driving range and the energy consumption of a pure electric vehicle according to claim 1, wherein the step of calculating the time required for the battery power to be reduced to the set battery power according to the set battery power, and the step of obtaining the first running time comprises the steps of:
DS1 and CSSM working conditions of a shortening method are carried out on the driving range simulation model;
counting the battery electric quantity at each moment in the DS1 and CSSM working conditions to obtain a time-varying curve of the battery electric quantity;
substituting the set battery electric quantity into the time-varying curve of the battery electric quantity, and calculating the time required for the battery electric quantity to be reduced to the set battery electric quantity to obtain the first running time.
3. The method for simulating and analyzing the driving range and the energy consumption of the pure electric vehicle according to claim 1, wherein the method for setting the first operation time to be the total operation time of the shortened method DS1 and CSSM working conditions is as follows:
setting the time at which the shortening method starts to be zero;
calculating the starting operation time of the DS2 working condition according to the zero time and the first operation time to obtain a first operation time;
starting from the moment of starting the shortening method to the first operation moment, carrying out DS1 and CSSM working conditions;
and from the first operation time, DS2 working conditions and CSSE working conditions are sequentially carried out.
4. The method for simulating and analyzing the driving range and the energy consumption of the pure electric vehicle according to claim 1, wherein the DS1 comprises: a first circulation driving condition and a second circulation driving condition; the DS2 includes: a third cycle running condition and a fourth cycle running condition;
the driving mileage during DS1 operating mode includes: the driving range simulation model simulates a first driving range obtained by the electric automobile in the first cycle driving condition process; a second driving range during a second cycle driving condition;
the energy consumption during DS1 operation includes: first energy consumption during a first cycle running condition; the second energy consumption in the second cycle driving working condition process;
the driving mileage during DS2 operating mode includes: a third driving range during a third cycle driving condition; a fourth driving range during a fourth cycle driving condition;
the energy consumption during DS2 operation includes: third energy consumption during a third cycle driving condition; and fourth energy consumption during fourth cycle driving conditions.
5. The method for simulating and analyzing the driving range and the energy consumption of the pure electric vehicle according to claim 4, wherein the hundred kilometers of the energy consumption of the electric vehicle is calculated by a formula I;
formula one;
wherein EC_100 is hundred kilometers of energy consumption, E_DC1 is first energy consumption, E_DC2 is second energy consumption, E_DC3 is third energy consumption, E_DC4 is fourth energy consumption, S 1 、S 2 、S 3 、S 4 The first driving distance, the second driving distance, the third driving distance, the fourth driving distance and the E_REESS are the total energy consumption of the whole working condition of the shortening method respectively.
6. The method for simulating and analyzing the driving range and the energy consumption of the pure electric vehicle according to claim 5, wherein the driving range of the electric vehicle is calculated by a formula II;
a second formula;
wherein BER is the driving range, EC_100 is hundred kilometers of energy consumption, and E_REESS is the total energy consumption of the whole working condition of the shortening method.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106326581A (en) * | 2016-08-29 | 2017-01-11 | 北京新能源汽车股份有限公司 | Determination method and device for driving range and automobile |
| US20190101934A1 (en) * | 2017-10-04 | 2019-04-04 | Here Global B.V. | Link level wind factor computation for efficient drone routing using 3d city map data |
| CN110532634A (en) * | 2019-08-02 | 2019-12-03 | 宝能汽车有限公司 | Energy consumption of vehicles and the emulation mode of continual mileage, system and vehicle |
| CN112406630A (en) * | 2020-11-30 | 2021-02-26 | 的卢技术有限公司 | Electric vehicle driving range calculation method based on working condition identification |
| CN112444750A (en) * | 2020-09-23 | 2021-03-05 | 中汽研汽车检验中心（天津）有限公司 | Method for quickly testing driving range of electric automobile |
| CN113901581A (en) * | 2021-11-20 | 2022-01-07 | 长安马自达汽车有限公司 | Method for calculating endurance mileage of electric automobile |
| CN114993708A (en) * | 2022-06-30 | 2022-09-02 | 阿波罗智能技术(北京)有限公司 | Method and device for determining driving range of vehicle |
-
2024
- 2024-01-17 CN CN202410067434.7A patent/CN117574694B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106326581A (en) * | 2016-08-29 | 2017-01-11 | 北京新能源汽车股份有限公司 | Determination method and device for driving range and automobile |
| US20190101934A1 (en) * | 2017-10-04 | 2019-04-04 | Here Global B.V. | Link level wind factor computation for efficient drone routing using 3d city map data |
| CN110532634A (en) * | 2019-08-02 | 2019-12-03 | 宝能汽车有限公司 | Energy consumption of vehicles and the emulation mode of continual mileage, system and vehicle |
| CN112444750A (en) * | 2020-09-23 | 2021-03-05 | 中汽研汽车检验中心（天津）有限公司 | Method for quickly testing driving range of electric automobile |
| CN112406630A (en) * | 2020-11-30 | 2021-02-26 | 的卢技术有限公司 | Electric vehicle driving range calculation method based on working condition identification |
| CN113901581A (en) * | 2021-11-20 | 2022-01-07 | 长安马自达汽车有限公司 | Method for calculating endurance mileage of electric automobile |
| CN114993708A (en) * | 2022-06-30 | 2022-09-02 | 阿波罗智能技术(北京)有限公司 | Method and device for determining driving range of vehicle |
Non-Patent Citations (1)
| Title |
|---|
| 刘忠途 等: "基于台架模拟的纯电动汽车能耗经济性研究", 中山大学学报(自然科学版), vol. 50, no. 01, 15 January 2011 (2011-01-15), pages 45 - 48 * |
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