Simulation Method, Device and Computer Storage Medium for Endurance Mileage

Abstract

Embodiments of the present application disclose a simulation method, device and computer storage medium for cruising range, belonging to the field of simulation technology. The method includes: obtaining a vehicle cruising range simulation model of an electric vehicle and energy recovery parameters of the electric vehicle, where the vehicle cruising range simulation model is used to simulate the cruising range of the battery of the electric vehicle; determining multiple different levels of energy recovery curves of the electric vehicle based on the energy recovery parameters of the electric vehicle; and simulating the cruising range of the electric vehicle based on the vehicle cruising range simulation model and the multiple different levels of energy recovery curves. By simulating with different levels of energy recovery curves and the vehicle cruising range simulation model, the embodiments of the present application take into account the influence of different recovery intensities on the cruising range, can quickly determine the optimal electric drive design scheme when achieving the target cruising range, and improve the comprehensiveness and reliability of the simulation.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of simulation technologies, and particularly to a method and device for simulating the cruising range and a computer storage medium. Background Art

[0002] With the increasing prominence of environmental problems, electric vehicles with pure electric systems and hybrid systems have gradually received attention due to their low environmental pollution. Among them, one of the main problems of pure electric systems and hybrid systems is the achievement of the target cruising range. Therefore, in order to determine whether the battery of an electric vehicle can reach the target cruising range, it is necessary to simulate the cruising range of the electric vehicle at the beginning of the design of the electric vehicle.

[0003] Currently, a cruising range simulation model of a vehicle can be established based on structural parameters such as the whole vehicle, battery, and electric drive, as well as the vehicle control strategy. The cruising range of the whole vehicle can be simulated through the cruising range simulation model of the whole vehicle, so as to determine whether the battery of the electric vehicle reaches the target cruising range within the expected discharge range.

[0004] However, since it is usually required to evaluate the cruising range ability of an electric vehicle using the NEDC cycle condition, the braking stage is in a uniform deceleration state, and the energy recovery intensity is relatively single. Therefore, the energy recovery strategy commonly used in simulation analysis is relatively simple, only considering maximizing energy recovery, without considering the influence of different recovery intensities on the cruising range, nor considering driving performance and safety factors, resulting in incomplete and unreliable simulation. Summary of the Invention

[0005] The embodiments of the present application provide a method and device for simulating the cruising range and a computer storage medium, which can be used to solve the problems of inaccurate, incomplete, and unreliable simulation results of the cruising range in the related art. The technical solutions are as follows:

[0006] On the one hand, a method for simulating the cruising range is provided. The method includes:

[0007] Obtain a cruising range simulation model of an electric vehicle and the energy recovery parameters of the electric vehicle. The cruising range simulation model of the whole vehicle is used to simulate the cruising range of the battery of the electric vehicle;

[0008] Based on the energy recovery parameters of the electric vehicle, determine multiple different levels of energy recovery curves of the electric vehicle;

[0009] Based on the cruising range simulation model of the whole vehicle and the multiple different levels of energy recovery curves, simulate the cruising range of the electric vehicle.

[0010] In some embodiments, the energy recovery parameters include at least one of the maximum energy recovery capacity of the motor of the electric vehicle, the vehicle driving experience data, and the braking requirements of the driving cycle conditions;

[0011] Determining multiple different levels of energy recovery curves for the electric vehicle based on the energy recovery parameters of the electric vehicle, including:

[0012] When the vehicle driving experience data is included in the energy recovery parameters, determining multiple different levels of energy recovery curves for the electric vehicle based on the maximum energy recovery capacity of the motor, the vehicle driving experience data, and the braking requirements of the driving cycle conditions;

[0013] When the vehicle driving experience data is not included in the energy recovery parameters, determining the maximum level of energy recovery curve for the electric vehicle based on the maximum energy recovery capacity of the motor and the braking requirements of the driving cycle conditions;

[0014] Determining the multiple different levels of energy recovery curves according to multiple different proportionality coefficients and the maximum level of energy recovery curve.

[0015] In some embodiments, simulating the cruising range of the electric vehicle based on the vehicle cruising range simulation model and the multiple different levels of energy recovery curves, including:

[0016] When the electric vehicle is in the vehicle matching design stage, based on the vehicle cruising range simulation model and the multiple different levels of energy recovery curves, performing cruising range simulations at different levels within a specified range of the battery SOC of the electric vehicle to obtain a first simulation result, where the first simulation result includes the maximum cruising range corresponding to the maximum level of energy recovery curve and the distribution of the motor operating points of the electric vehicle;

[0017] When the maximum cruising range does not meet the target cruising range, updating the vehicle cruising range simulation model according to the maximum cruising range and the distribution of the motor operating points, and returning to the operation of simulating the cruising range of the electric vehicle based on the vehicle cruising range simulation model and the multiple different levels of energy recovery curves until the maximum cruising range meets the target cruising range.

[0018] In some embodiments, simulating the cruising range of the electric vehicle based on the vehicle cruising range simulation model and the multiple different levels of energy recovery curves, including:

[0019] When the electric vehicle is in the vehicle calibration stage, obtaining energy adjustment parameters;

[0020] Update the energy recovery curves of the multiple different levels according to the energy adjustment parameter;

[0021] Based on the updated energy recovery curves and the vehicle endurance mileage simulation model, simulate the endurance mileage of the electric vehicle under the target cycle condition.

[0022] In some embodiments, before simulating the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the energy recovery curves of the multiple different levels, it further includes:

[0023] When the electric vehicle is in the vehicle calibration stage, obtain the driving experiment data of the electric vehicle;

[0024] Calibrate the vehicle endurance mileage simulation model according to the driving experiment data;

[0025] When the second simulation result of the vehicle endurance mileage simulation model meets the calibration requirements, perform the operation of simulating the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the energy recovery curves of the multiple different levels.

[0026] In some embodiments, after calibrating the vehicle endurance mileage simulation model according to the driving experiment data, it further includes:

[0027] When the second simulation result does not meet the calibration requirements, update the vehicle endurance mileage simulation model, and return to the operation of calibrating the vehicle endurance mileage simulation model according to the driving experiment data until the second simulation result meets the calibration requirements.

[0028] On the other hand, a simulation device for endurance mileage is provided, and the device includes:

[0029] A first acquisition module, configured to acquire a vehicle endurance mileage simulation model of an electric vehicle and the energy recovery parameters of the electric vehicle, where the vehicle endurance mileage simulation model is used to simulate the endurance mileage of the battery of the electric vehicle;

[0030] A determination module, configured to determine the energy recovery curves of multiple different levels of the electric vehicle based on the energy recovery parameters of the electric vehicle;

[0031] A simulation module, configured to simulate the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the energy recovery curves of the multiple different levels.

[0032] In some embodiments, the energy recovery parameters include at least one of the maximum recovery ability of the motor of the electric vehicle, the vehicle driving experience data, and the braking requirements of the cycle condition;

[0033] The determining module is configured to:

[0034] When the vehicle driving experience data is included in the energy recovery parameters, based on the maximum motor recovery capacity, the vehicle driving experience data, and the braking requirements of the cycle condition, determine multiple different levels of energy recovery curves for the electric vehicle;

[0035] When the vehicle driving experience data is not included in the energy recovery parameters, based on the maximum motor recovery capacity and the braking requirements of the cycle condition, determine the maximum level of energy recovery curve for the electric vehicle;

[0036] According to multiple different proportionality coefficients and the maximum level of energy recovery curve, determine the multiple different levels of energy recovery curves.

[0037] In some embodiments, the simulation module is configured to:

[0038] When the electric vehicle is in the vehicle matching design stage, based on the vehicle endurance mileage simulation model and the multiple different levels of energy recovery curves, perform endurance mileage simulation at different levels within a specified range of the battery SOC of the electric vehicle to obtain a first simulation result, where the first simulation result includes the maximum endurance mileage corresponding to the maximum level of energy recovery curve and the distribution of the motor operating points of the electric vehicle;

[0039] When the maximum endurance mileage does not meet the target endurance mileage, update the vehicle endurance mileage simulation model according to the maximum endurance mileage and the distribution of the motor operating points, and return to the operation of performing endurance mileage simulation on the electric vehicle based on the vehicle endurance mileage simulation model and the multiple different levels of energy recovery curves until the maximum endurance mileage meets the target endurance mileage.

[0040] In some embodiments, the simulation module is configured to:

[0041] When the electric vehicle is in the vehicle calibration stage, obtain energy adjustment parameters;

[0042] According to the energy adjustment parameters, update the multiple different levels of energy recovery curves;

[0043] Based on the updated energy recovery curves and the vehicle endurance mileage simulation model, perform endurance mileage simulation of the electric vehicle under the target cycle condition.

[0044] In some embodiments, the device further includes:

[0045] A second acquisition module, configured to acquire driving experiment data of the electric vehicle when the electric vehicle is in the vehicle calibration stage;

[0046] A calibration module, configured to calibrate the vehicle endurance mileage simulation model according to the driving experiment data;

[0047] A trigger module, configured to, when a second simulation result of the vehicle endurance mileage simulation model meets the calibration requirements, the simulation module simulate the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the multiple different-level energy recovery curves.

[0048] In some embodiments, the device further includes:

[0049] An update module, configured to update the vehicle endurance mileage simulation model when the second simulation result does not meet the calibration requirements, and the calibration module calibrates the vehicle endurance mileage simulation model according to the driving experiment data until the second simulation result meets the calibration requirements.

[0050] On the other hand, a computer-readable storage medium is provided, on which instructions are stored, and when the instructions are executed by a processor, any step in the above-mentioned endurance mileage simulation method is implemented.

[0051] The beneficial effects brought by the technical solutions provided in the embodiments of the present application at least include:

[0052] In the embodiments of the present application, by combining different-level energy recovery curves with the vehicle endurance mileage simulation model for simulation, the influence of different recovery intensities on the endurance mileage is taken into account, which can not only quickly determine the optimal electric drive design scheme when achieving the target endurance mileage, but also improve the comprehensiveness and reliability of the simulation. Description of the Drawings

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0054] Figure 1 is a flowchart of a method for simulating endurance mileage provided by an embodiment of the present application;

[0055] Figure 2 is a flowchart of another method for simulating endurance mileage provided by an embodiment of the present application;

[0056] Figure 3It is a schematic diagram of energy recovery curves at different levels provided by an embodiment of the present application;

[0057] Figure 4 It is a schematic structural diagram of a simulation device for cruising range provided by an embodiment of the present application;

[0058] Figure 5 It is a schematic structural diagram of another simulation device for cruising range provided by an embodiment of the present application;

[0059] Figure 6 It is a schematic structural diagram of another simulation device for cruising range provided by an embodiment of the present application;

[0060] Figure 7 It is a schematic structural diagram of a terminal provided by an embodiment of the present application. Detailed implementation manners

[0061] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will further describe the embodiments of the present application in detail with reference to the accompanying drawings.

[0062] Before explaining in detail a simulation method for cruising range provided by an embodiment of the present application, an application scenario provided by an embodiment of the present application will be explained first.

[0063] The energy recovery of an electric vehicle means that when the electric vehicle decelerates, the wheels drive the drive motor to rotate, and the motor becomes an alternator to generate current. The alternating current is rectified into direct current by the motor controller to charge the power battery pack (braking regenerative energy).

[0064] The energy recovery of an electric vehicle has an important impact on the cruising ability of the electric vehicle. However, currently, when simulating and analyzing the cruising range of an electric vehicle, it is usually required to use the NEDC cycle condition to evaluate the cruising range ability of the electric vehicle. The braking stage is in a uniform deceleration state, and the energy recovery intensity is relatively single. Therefore, the energy recovery strategy generally adopted in the simulation analysis is relatively simple, only considering maximizing energy recovery, without considering the impact of different recovery intensities on the cruising range, nor considering driving performance and safety factors, resulting in incomplete and unreliable simulation.

[0065] Based on such an application scenario, an embodiment of the present application provides a simulation method for cruising range that improves the accuracy and reliability of simulation.

[0066] Figure 1 It is a flowchart of a simulation method for cruising range provided by an embodiment of the present application. The simulation method for cruising range may include the following steps:

[0067] Step 101: Obtain the simulation model of the overall vehicle endurance mileage of the electric vehicle and the energy recovery parameters of the electric vehicle. The simulation model of the overall vehicle endurance mileage is used to simulate the endurance mileage of the battery of the electric vehicle.

[0068] Step 102: Determine multiple different levels of energy recovery curves of the electric vehicle based on the energy recovery parameters of the electric vehicle.

[0069] Step 103: Simulate the endurance mileage of the electric vehicle based on the simulation model of the overall vehicle endurance mileage and the multiple different levels of energy recovery curves.

[0070] In the embodiment of the present application, by combining energy recovery curves of different levels with the simulation model of the overall vehicle endurance mileage for simulation, the influence of different recovery intensities on the endurance mileage is taken into account. It can not only quickly determine the optimal electric drive design scheme when achieving the target endurance mileage, but also improve the comprehensiveness and reliability of the simulation.

[0071] In some embodiments, the energy recovery parameters include at least one of the maximum recovery capacity of the motor of the electric vehicle, the overall vehicle driving experience data, and the braking requirements of the cycle condition.

[0072] Determining multiple different levels of energy recovery curves of the electric vehicle based on the energy recovery parameters of the electric vehicle includes:

[0073] When the energy recovery parameters include the overall vehicle driving experience data, determine multiple different levels of energy recovery curves of the electric vehicle based on the maximum recovery capacity of the motor, the overall vehicle driving experience data, and the braking requirements of the cycle condition;

[0074] When the energy recovery parameters do not include the overall vehicle driving experience data, determine the maximum level of energy recovery curve of the electric vehicle based on the maximum recovery capacity of the motor and the braking requirements of the cycle condition;

[0075] Determine the multiple different levels of energy recovery curves according to multiple different proportionality coefficients and the maximum level of energy recovery curve.

[0076] In some embodiments, simulating the endurance mileage of the electric vehicle based on the simulation model of the overall vehicle endurance mileage and the multiple different levels of energy recovery curves includes:

[0077] When the electric vehicle is in the vehicle matching design stage, based on the vehicle endurance mileage simulation model and the energy recovery curves of multiple different levels, the endurance mileage simulation under different levels is carried out within the specified range of the battery SOC of the electric vehicle to obtain a first simulation result, and the first simulation result includes the maximum endurance mileage corresponding to the energy recovery curve of the maximum level and the distribution of the motor operating points of the electric vehicle;

[0078] When the maximum endurance mileage does not meet the target endurance mileage, update the vehicle endurance mileage simulation model according to the maximum endurance mileage and the distribution of the motor operating points, and return the operation of simulating the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the energy recovery curves of multiple different levels until the maximum endurance mileage meets the target endurance mileage.

[0079] In some embodiments, simulating the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the energy recovery curves of multiple different levels includes:

[0080] When the electric vehicle is in the vehicle calibration stage, obtain energy adjustment parameters;

[0081] Update the energy recovery curves of multiple different levels according to the energy adjustment parameters;

[0082] Based on the updated energy recovery curves and the vehicle endurance mileage simulation model, simulate the endurance mileage of the electric vehicle under the target cycle condition.

[0083] In some embodiments, before simulating the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the energy recovery curves of multiple different levels, it further includes:

[0084] When the electric vehicle is in the vehicle calibration stage, obtain the driving experiment data of the electric vehicle;

[0085] Calibrate the vehicle endurance mileage simulation model according to the driving experiment data;

[0086] When the second simulation result of the vehicle endurance mileage simulation model meets the calibration requirements, perform the operation of simulating the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the energy recovery curves of multiple different levels.

[0087] In some embodiments, after calibrating the vehicle endurance mileage simulation model according to the driving experiment data, it further includes:

[0088] When the second simulation result does not meet the benchmarking requirements, update the vehicle endurance mileage simulation model, and return the operation of benchmarking the vehicle endurance mileage simulation model according to the driving experiment data until the second simulation result meets the benchmarking requirements.

[0089] All of the above optional technical solutions can be combined arbitrarily to form optional embodiments of the present application, and the embodiments of the present application will not elaborate on them one by one.

[0090] Figure 2 It is a flowchart of a simulation method for endurance mileage provided by an embodiment of the present application. In this embodiment, an example is given where the simulation method for endurance mileage is applied to a terminal. The simulation method for endurance mileage may include the following steps:

[0091] Step 201: The terminal obtains a vehicle endurance mileage simulation model of an electric vehicle and energy recovery parameters of the electric vehicle.

[0092] It should be noted that the vehicle endurance mileage simulation model is used to simulate the endurance mileage of the battery of an electric vehicle, and the vehicle endurance mileage simulation model can simulate the endurance mileage of the battery of an electric vehicle under different vehicle matching design schemes.

[0093] Since the endurance mileage of an electric vehicle is related to the energy recovery parameters of the electric vehicle, in addition to obtaining the vehicle endurance mileage simulation model of the electric vehicle, the terminal also needs to obtain the energy recovery parameters of the electric vehicle. The energy recovery parameters include at least one of the maximum recovery capacity (including maximum recovery torque) of the motor of the electric vehicle, vehicle driving experience data, and braking requirements for cycle conditions, etc.

[0094] In some embodiments, when receiving a first acquisition instruction, the terminal can obtain the built vehicle endurance mileage simulation model of the electric vehicle and the energy recovery parameters of the electric vehicle from a storage file or other devices, and load the vehicle endurance mileage simulation model into the corresponding simulation application program. Alternatively, when receiving a first acquisition instruction, the terminal obtains the built vehicle endurance mileage simulation model of the electric vehicle from a storage file, and when receiving a second acquisition instruction, obtains the energy recovery parameters of the electric vehicle carried in the second acquisition instruction.

[0095] It should be noted that the terminal can receive the first acquisition instruction or the second acquisition instruction in the currently running simulation application program, and the first acquisition instruction and the second acquisition instruction are triggered when the user performs a specified operation on the display interface of the simulation application program. The specified operation can be a click operation, a voice operation, a sliding operation, etc.

[0096] In some embodiments, the terminal can not only obtain the vehicle endurance simulation model when receiving the first acquisition instruction, but also build the vehicle endurance simulation model of the electric vehicle when receiving the building instruction.

[0097] In some embodiments, when receiving the building instruction, the terminal builds the vehicle endurance simulation model according to parameters such as the electric drive and battery of the electric vehicle and the vehicle control strategy. And when building, it can perform co-simulation after building based on one-dimensional simulation software such as CRUISE / Amesim and MATLAB / simulink, or build and simulate only based on MATLAB / simulink.

[0098] It should be noted that the operation of the terminal to build the vehicle endurance simulation model can refer to related technologies, and the embodiments of the present application will not elaborate on this one by one. The building instruction is triggered when the user acts on the display interface of the corresponding simulation application through a specified operation.

[0099] In some embodiments, before building the vehicle endurance simulation module in the simulation application, the terminal can also receive a start instruction and run the simulation application according to the start instruction.

[0100] It should be noted that the start instruction is also triggered when the user acts on the identifier of the simulation application displayed on the terminal through a specified operation, and the identifier of the simulation application can be an image identifier and / or a text identifier.

[0101] Step 202: The terminal determines multiple different levels of energy recovery curves of the electric vehicle based on the energy recovery parameters of the electric vehicle.

[0102] In order to accurately simulate the endurance mileage of the electric vehicle, the terminal can obtain multiple different levels of energy recovery curves of the electric vehicle, that is, the terminal can determine multiple different levels of energy recovery curves of the electric vehicle based on the energy recovery parameters of the electric vehicle.

[0103] It should be noted that the multiple different levels of energy recovery curves describe different recovery intensities of the electric vehicle, and different recovery intensities of the electric vehicle can be described by different recovery torques.

[0104] As can be seen from the above, the energy recovery parameters include at least one of the maximum recovery ability of the electric vehicle motor, vehicle driving experience data, and cyclic working condition braking requirements. The operations of the terminal to determine multiple different levels of energy recovery curves of the electric vehicle are different when the parameters included in the energy recovery parameters are different.

[0105] As an example, the terminal determines multiple different levels of energy recovery curves for the electric vehicle based on the energy recovery parameters of the electric vehicle, including: when the energy recovery parameters include the vehicle driving experience data, determining multiple different levels of energy recovery curves for the electric vehicle based on the maximum motor recovery capacity, the vehicle driving experience data, and the braking requirements of the driving cycle; when the energy recovery parameters do not include the vehicle driving experience data, determining the maximum level of energy recovery curve for the electric vehicle based on the maximum motor recovery capacity and the braking requirements of the driving cycle; and determining multiple different levels of energy recovery curves according to multiple different proportionality coefficients and the maximum level of energy recovery curve.

[0106] In some embodiments, the multiple different levels of energy recovery curves determined based on the vehicle driving experience data may be as Figure 3 shown. Among the multiple different levels of energy recovery curves, when the vehicle speed is low (the vehicle speed is between 0 - 15 km / h (kilometers per hour)), all the braking torque of the electric vehicle is borne by mechanical braking; when the vehicle speed is medium - low (the vehicle speed is between 15 - 50 km / h), the motor recovery torque gradually increases; when the vehicle speed is medium - high (the vehicle speed is between 50 km / h - 120 km / h), the motor recovery torque and mechanical braking maintain the same recovery intensity; when the vehicle speed is ultra - high (the vehicle speed is greater than 120 km / h), the motor recovery torque gradually decreases to not participate in energy recovery to ensure driving performance and safety.

[0107] In some embodiments, different levels of energy recovery curves refer to energy recovery curves with different intensities. Generally, the maximum level of energy recovery curve is called the first - level energy recovery curve, the next - level energy recovery curve is called the second - level energy recovery curve, the next - level energy recovery curve after that is called the third - level energy recovery curve, and so on.

[0108] In some embodiments, when the energy recovery parameters do not include the vehicle driving experience data, generally, the peak torque of the second - level energy recovery curve is set between 0.7 - 0.8 of the peak torque of the first - level energy recovery curve, and the peak torque of the third - level energy recovery curve is set between 0.4 - 0.6 of the peak torque of the first - level energy recovery curve. That is, the proportionality coefficient between the second - level energy recovery curve and the first - level energy recovery curve is 0.7 - 0.8, and the proportionality coefficient between the third - level energy recovery curve and the first - level energy recovery curve is 0.4 - 0.6, etc.

[0109] Step 203: The terminal simulates the driving range of the electric vehicle based on the vehicle driving range simulation model and multiple different levels of energy recovery curves.

[0110] As an example, the operations of the terminal for simulating the cruising range of an electric vehicle based on a vehicle cruising range simulation model and multiple energy recovery curves of different levels include: when the electric vehicle is in the vehicle matching design stage, based on the vehicle cruising range simulation model and multiple energy recovery curves of different levels, perform cruising range simulations at different levels within the specified range of the battery SOC (State of Charge) of the electric vehicle to obtain a first simulation result. The first simulation result includes the maximum cruising range corresponding to the maximum-level energy recovery curve and the distribution of the motor operating points of the electric vehicle; when the maximum cruising range does not meet the target cruising range, update the vehicle cruising range simulation model according to the maximum cruising range and the distribution of the motor operating points, and return to the operation of simulating the cruising range of the electric vehicle based on the vehicle cruising range simulation model and multiple energy recovery curves of different levels until the maximum cruising range meets the target cruising range.

[0111] In order to enable the cruising range of the electric vehicle to reach the target cruising range, it is necessary to verify whether the design of the electric vehicle can reach the target cruising range during the vehicle matching design stage of the electric vehicle. Therefore, when the terminal is in the vehicle matching design stage, if the maximum cruising range of the electric vehicle cannot reach the target cruising range after simulation, it is necessary to update the vehicle cruising range simulation model until the maximum cruising range of the electric vehicle meets the target cruising range.

[0112] In some embodiments, that the maximum cruising range of the electric vehicle meets the target cruising range means that the maximum cruising range of the electric vehicle is greater than or equal to the target cruising range.

[0113] Exemplarily, the specified range of the battery SOC is set in advance according to requirements, and different types of electric vehicles have different specified ranges. For example, when the electric vehicle is a hybrid vehicle, the allowable use range of the battery SOC of the electric vehicle is 95% - 20%, and when the electric vehicle is a pure electric vehicle, the allowable use range of the battery SOC of the electric vehicle is 95% - 5%.

[0114] In some embodiments, when the maximum cruising range of the electric vehicle meets the target cruising range, the corresponding vehicle matching design scheme at this time can be determined as the best matching design scheme of the electric vehicle.

[0115] It should be noted that the operations of the terminal for performing cruising range simulations at different levels within the specified range of the battery SOC of the electric vehicle based on the vehicle cruising range simulation model and multiple energy recovery curves of different levels can refer to related technologies, and the embodiments of the present application will not elaborate on this one by one.

[0116] In some embodiments, the first simulation result includes not only the maximum cruising range corresponding to the energy recovery curve of the maximum level and the distribution of the motor operating points of the electric vehicle, but also the system comprehensive efficiency of the electric vehicle's regenerative braking energy recovery system, the mechanical braking torque under the cycle condition, the regenerative braking energy recovery efficiency, etc. Therefore, the terminal evaluates the first simulation result based on the distribution of the motor operating points, the system comprehensive efficiency, the regenerative braking energy recovery efficiency, the mileage contribution rate of the regenerative braking energy recovery system, the distribution ratio of the recovered energy (recovered torque), etc., so as to determine whether the energy grading is reasonable. For example, the terminal can evaluate according to whether the distribution of the motor operating points belongs to concentrated distribution or dispersed distribution, whether the mechanical braking torque under the cycle condition is greater than the torque threshold, whether the regenerative braking energy recovery efficiency and the system comprehensive efficiency are greater than the efficiency threshold, and / or whether the mileage contribution rate of the regenerative braking energy recovery system is greater than the contribution rate threshold.

[0117] In some embodiments, after obtaining the first simulation result, the terminal can display the first simulation result in the form of a radar chart.

[0118] In some embodiments, when the energy grading is unreasonable, the terminal can adjust the energy recovery curve and return to the operation in step 203.

[0119] It should be noted that the terminal can not only perform simulation when the electric vehicle is in the vehicle matching design stage, but also perform simulation when the electric vehicle is in the integration calibration stage.

[0120] As an example, the operation of the terminal to simulate the cruising range of the electric vehicle based on the vehicle cruising range simulation model and multiple energy recovery curves of different levels includes: when the electric vehicle is in the vehicle calibration stage, obtaining the energy adjustment parameter; updating the multiple energy recovery curves of different levels according to the energy adjustment parameter; and simulating the cruising range of the electric vehicle under the target cycle condition based on the updated energy recovery curves and the vehicle cruising range simulation model.

[0121] Since in the vehicle calibration stage, different users have different driving experiences for the electric vehicle, and according to different driving experiences, there may be different requirements for the energy recovery curve. Therefore, the terminal may obtain the energy adjustment parameter and update the multiple energy recovery curves when obtaining the energy adjustment parameter.

[0122] It should be noted that the energy adjustment parameter includes a proportional coefficient, a vehicle speed range, etc.

[0123] In some embodiments, in the vehicle calibration stage, when the terminal simulates the cruising range of the electric vehicle under the target cycle condition based on the updated energy recovery curves and the vehicle cruising range simulation model, the initial value of the SOC of the battery is set between 50% and 80%.

[0124] In some embodiments, to improve the simulation progress, when the electric vehicle is in the vehicle calibration stage, the terminal can obtain the driving experiment data of the electric vehicle; calibrate the vehicle endurance mileage simulation model according to the driving experiment data to obtain a second simulation result; when the second simulation result of the vehicle endurance mileage simulation model meets the calibration requirements, perform the operation of step 203 above.

[0125] It should be noted that the driving experiment data includes the driving data of the electric vehicle under a single cycle condition. The second simulation result includes the vehicle speed of the electric vehicle, the voltage / current / SOC of the battery, the speed / torque of the motor, etc. The calibration requirements include that the following error of the vehicle speed of the electric vehicle does not exceed 0.5 km / h, and the following error of the voltage / current / SOC of the battery and the speed / torque of the motor is between 2% and 5%.

[0126] In some embodiments, when the second simulation result does not meet the calibration requirements, update the vehicle endurance mileage simulation model, and return to the operation of calibrating the vehicle endurance mileage simulation model according to the driving experiment data until the second simulation result meets the calibration requirements.

[0127] In some embodiments, after the terminal performs simulation in the vehicle calibration stage, a third simulation result is obtained, and this third simulation result can be used as the vehicle driving experience data of other electric vehicles.

[0128] In the embodiments of the present application, by combining energy recovery curves of different levels with the vehicle endurance mileage simulation model for simulation, the influence of different recovery intensities on the endurance mileage is considered, and not only can the optimal electric drive design scheme when achieving the target endurance mileage be quickly determined. In addition, the terminal can not only perform endurance mileage prediction analysis according to the initially formulated energy recovery curves of different levels in the vehicle matching design stage, but also perform cycle condition simulation analysis according to the vehicle endurance mileage simulation model in the vehicle calibration stage to optimize the comprehensive performance of the endurance mileage and drivability, thereby improving the comprehensiveness and reliability of the simulation.

[0129] Figure 4 It is a schematic structural diagram of a simulation device for endurance mileage provided by an embodiment of the present application. The simulation device for endurance mileage can be implemented by software, hardware, or a combination of both. The simulation device for endurance mileage may include: a first acquisition module 401, a determination module 402, and a simulation module 403.

[0130] The first acquisition module 401 is configured to acquire the vehicle endurance mileage simulation model of the electric vehicle and the energy recovery parameters of the electric vehicle, and the vehicle endurance mileage simulation model is used to simulate the endurance mileage of the battery of the electric vehicle;

[0131] A determination module 402, configured to determine multiple different levels of energy recovery curves of the electric vehicle based on the energy recovery parameters of the electric vehicle;

[0132] A simulation module 403, configured to simulate the cruising range of the electric vehicle based on the vehicle cruising range simulation model and the multiple different levels of energy recovery curves.

[0133] In some embodiments, the energy recovery parameters include at least one of the maximum energy recovery capacity of the motor of the electric vehicle, the vehicle driving experience data, and the braking requirements of the driving cycle conditions;

[0134] The determination module 402 is configured to:

[0135] When the energy recovery parameters include the vehicle driving experience data, determine multiple different levels of energy recovery curves of the electric vehicle based on the maximum energy recovery capacity of the motor, the vehicle driving experience data, and the braking requirements of the driving cycle conditions;

[0136] When the energy recovery parameters do not include the vehicle driving experience data, determine the maximum level of energy recovery curve of the electric vehicle based on the maximum energy recovery capacity of the motor and the braking requirements of the driving cycle conditions;

[0137] Determine the multiple different levels of energy recovery curves according to multiple different scale factors and the maximum level of energy recovery curve.

[0138] In some embodiments, the simulation module 403 is configured to:

[0139] When the electric vehicle is in the vehicle matching design stage, based on the vehicle cruising range simulation model and the multiple different levels of energy recovery curves, perform cruising range simulations at different levels within a specified range of the battery SOC of the electric vehicle to obtain a first simulation result, where the first simulation result includes the maximum cruising range corresponding to the maximum level of energy recovery curve and the distribution of the motor operating points of the electric vehicle;

[0140] When the maximum cruising range does not meet the target cruising range, update the vehicle cruising range simulation model according to the maximum cruising range and the distribution of the motor operating points, and return to the operation of simulating the cruising range of the electric vehicle based on the vehicle cruising range simulation model and the multiple different levels of energy recovery curves until the maximum cruising range meets the target cruising range.

[0141] In some embodiments, the simulation module 403 is configured to:

[0142] When the electric vehicle is in the vehicle calibration stage, obtain energy adjustment parameters;

[0143] Update the energy recovery curves of the multiple different levels according to the energy adjustment parameter;

[0144] Based on the updated energy recovery curves and the vehicle endurance mileage simulation model, simulate the endurance mileage of the electric vehicle under the target cycle condition.

[0145] In some embodiments, refer to Figure 5 , the device further includes:

[0146] A second acquisition module 404, configured to acquire the driving experiment data of the electric vehicle when the electric vehicle is in the vehicle calibration stage;

[0147] A calibration module 405, configured to calibrate the vehicle endurance mileage simulation model according to the driving experiment data;

[0148] A trigger module 406, configured to, when the second simulation result of the vehicle endurance mileage simulation model meets the calibration requirements, the simulation module 403 simulate the endurance mileage of the electric vehicle based on the vehicle endurance mileage simulation model and the energy recovery curves of the multiple different levels.

[0149] In some embodiments, refer to Figure 6 , the device further includes:

[0150] An update module 407, configured to, when the second simulation result does not meet the calibration requirements, update the vehicle endurance mileage simulation model, and the calibration module 405 calibrates the vehicle endurance mileage simulation model according to the driving experiment data until the second simulation result meets the calibration requirements.

[0151] In the embodiments of the present application, by combining the energy recovery curves of different levels with the vehicle endurance mileage simulation model for simulation, the influence of different recovery intensities on the endurance mileage is considered, and not only can the best electric drive design scheme when achieving the target endurance mileage be quickly determined. In addition, the terminal can not only perform endurance mileage prediction analysis according to the initially formulated energy recovery curves of different levels during the vehicle matching design stage, but also perform cycle condition simulation analysis according to the vehicle endurance mileage simulation model during the vehicle calibration stage to optimize the comprehensive performance of the endurance mileage and drivability, thereby improving the comprehensiveness and reliability of the simulation.

[0152] It should be noted that: When the above-described endurance mileage simulation device performs endurance mileage simulation, only the division of the above functional modules is used for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the endurance mileage simulation device provided in the above embodiment and the endurance mileage simulation method embodiment belong to the same concept. For the specific implementation process, please refer to the method embodiment and will not be elaborated here.

[0153] Figure 7 FIG. shows a structural block diagram of a terminal 700 provided by an exemplary embodiment of the present application. The terminal 700 may be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer, or a desktop computer. The terminal 700 may also be referred to by other names such as a user equipment, a portable terminal, a laptop terminal, a desktop terminal, etc.

[0154] Generally, the terminal 700 includes: a processor 701 and a memory 702.

[0155] The processor 701 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 701 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 701 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the wake state, also known as the CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 701 may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 701 may further include an AI (Artificial Intelligence) processor, and the AI processor is used to process computational operations related to machine learning.

[0156] The memory 702 may include one or more computer-readable storage media, which may be non-transitory. The memory 702 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash storage devices. In some embodiments, the non-transitory computer-readable storage media in the memory 702 is used to store at least one instruction for being executed by the processor 701 to implement the simulation method for the cruising range provided in the method embodiments of the present application.

[0157] In some embodiments, the terminal 700 may further optionally include: a peripheral device interface 703 and at least one peripheral device. The processor 701, the memory 702, and the peripheral device interface 703 may be connected through a bus or signal lines. Each peripheral device may be connected to the peripheral device interface 703 through a bus, signal lines, or a circuit board. Specifically, the peripheral device includes at least one of a radio frequency circuit 704, a display screen 705, a camera assembly 706, an audio circuit 707, a positioning assembly 708, and a power supply 709.

[0158] The peripheral device interface 703 may be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 701 and the memory 702. In some embodiments, the processor 701, the memory 702, and the peripheral device interface 703 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 701, the memory 702, and the peripheral device interface 703 may be implemented on a separate chip or circuit board, and the present embodiment does not limit this.

[0159] The radio frequency circuit 704 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 704 communicates with a communication network and other communication devices through electromagnetic signals. The radio frequency circuit 704 converts an electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 704 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so on. The radio frequency circuit 704 may communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: a metropolitan area network, each generation of mobile communication networks (2G, 3G, 4G, and 5G), a wireless local area network, and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 704 may further include a circuit related to NFC (Near Field Communication), and the present application does not limit this.

[0160] The display screen 705 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 705 is a touch display screen, the display screen 705 also has the ability to collect touch signals on or above the surface of the display screen 705. The touch signals can be input to the processor 701 as control signals for processing. At this time, the display screen 705 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, there may be one display screen 705, which is provided on the front panel of the terminal 700; in other embodiments, there may be at least two display screens 705, which are respectively provided on different surfaces of the terminal 700 or in a folded design; in other embodiments, the display screen 705 may be a flexible display screen, which is provided on the curved surface or the folding surface of the terminal 700. Even, the display screen 705 can also be set to an irregular non-rectangular shape, that is, a special-shaped screen. The display screen 705 can be prepared from materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0161] The camera module 706 is used to collect images or videos. Optionally, the camera module 706 includes a front camera and a rear camera. Generally, the front camera is provided on the front panel of the terminal, and the rear camera is provided on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth-of-field camera, a wide-angle camera, and a telephoto camera, so as to realize the function of background blurring by fusing the main camera and the depth-of-field camera, the function of panoramic shooting by fusing the main camera and the wide-angle camera, and the VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera module 706 may further include a flash. The flash can be a single-color-temperature flash or a two-color-temperature flash. The two-color-temperature flash refers to the combination of a warm-light flash and a cold-light flash, which can be used for light compensation under different color temperatures.

[0162] The audio circuit 707 may include a microphone and a speaker. The microphone is used to collect sound waves of the user and the environment, and convert the sound waves into electrical signals for input to the processor 701 for processing, or input to the radio frequency circuit 704 to enable voice communication. For the purpose of stereo collection or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal 700. The microphone may also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert the electrical signal from the processor 701 or the radio frequency circuit 704 into sound waves. The speaker may be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for uses such as ranging. In some embodiments, the audio circuit 707 may also include a headphone jack.

[0163] The positioning component 708 is used to locate the current geographical location of the terminal 700 to implement navigation or LBS (Location Based Service). The positioning component 708 may be a positioning component based on the GPS (Global Positioning System) of the United States, the Beidou system of China, the GLONASS system of Russia, or the Galileo system of the European Union.

[0164] The power supply 709 is used to supply power to each component in the terminal 700. The power supply 709 may be alternating current, direct current, a disposable battery, or a rechargeable battery. When the power supply 709 includes a rechargeable battery, the rechargeable battery may support wired charging or wireless charging. The rechargeable battery may also be used to support fast charging technology.

[0165] In some embodiments, the terminal 700 further includes one or more sensors 710. The one or more sensors 710 include but are not limited to: an acceleration sensor 711, a gyroscope sensor 712, a pressure sensor 713, a fingerprint sensor 714, an optical sensor 715, and a proximity sensor 716.

[0166] The acceleration sensor 711 can detect the magnitude of acceleration on the three coordinate axes of the coordinate system established with the terminal 700. For example, the acceleration sensor 711 can be used to detect the components of the gravitational acceleration on the three coordinate axes. The processor 701 can control the display screen 705 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 711. The acceleration sensor 711 can also be used for collecting game or user movement data.

[0167] The gyroscope sensor 712 can detect the body direction and rotation angle of the terminal 700. The gyroscope sensor 712 can cooperate with the acceleration sensor 711 to collect the 3D actions of the user on the terminal 700. Based on the data collected by the gyroscope sensor 712, the processor 701 can implement the following functions: motion sensing (such as changing the UI according to the user's tilting operation), image stabilization during shooting, game control, and inertial navigation.

[0168] The pressure sensor 713 can be disposed on the side frame of the terminal 700 and / or the lower layer of the display screen 705. When the pressure sensor 713 is disposed on the side frame of the terminal 700, it can detect the holding signal of the user on the terminal 700, and the processor 701 can perform left / right hand recognition or quick operation according to the holding signal collected by the pressure sensor 713. When the pressure sensor 713 is disposed on the lower layer of the display screen 705, the processor 701 can control the operable controls on the UI interface according to the pressure operation of the user on the display screen 705. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0169] The fingerprint sensor 714 is used to collect the fingerprints of the user. The processor 701 can identify the user's identity according to the fingerprints collected by the fingerprint sensor 714, or the fingerprint sensor 714 can identify the user's identity according to the collected fingerprints. When the identified user identity is a trusted identity, the processor 701 authorizes the user to perform relevant sensitive operations, and the sensitive operations include unlocking the screen, viewing encrypted information, downloading software, making payments, and changing settings, etc. The fingerprint sensor 714 can be disposed on the front, back, or side of the terminal 700. When there are physical buttons or manufacturer logos on the terminal 700, the fingerprint sensor 714 can be integrated with the physical buttons or manufacturer logos.

[0170] The optical sensor 715 is used to collect the ambient light intensity. In one embodiment, the processor 701 can control the display brightness of the display screen 705 according to the ambient light intensity collected by the optical sensor 715. Specifically, when the ambient light intensity is high, the display brightness of the display screen 705 is increased; when the ambient light intensity is low, the display brightness of the display screen 705 is decreased. In another embodiment, the processor 701 can also dynamically adjust the shooting parameters of the camera module 706 according to the ambient light intensity collected by the optical sensor 715.

[0171] The proximity sensor 716, also known as a distance sensor, is typically disposed on the front panel of the terminal 700. The proximity sensor 716 is used to collect the distance between the user and the front of the terminal 700. In one embodiment, when the proximity sensor 716 detects that the distance between the user and the front of the terminal 700 is gradually decreasing, the processor 701 controls the display screen 705 to switch from the lit state to the off state; when the proximity sensor 716 detects that the distance between the user and the front of the terminal 700 is gradually increasing, the processor 701 controls the display screen 705 to switch from the off state to the lit state.

[0172] Those skilled in the art can understand that Figure 7 the structure shown in

[0173] does not constitute a limitation on the terminal 700, and may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component layout.

[0174] The embodiments of the present application also provide a non-transitory computer-readable storage medium. When the instructions in the storage medium are executed by the processor of the terminal, the terminal can execute the simulation method for the cruising range provided in the above embodiments.

[0175] Those of ordinary skill in the art can understand that all or part of the steps for implementing the above embodiments can be completed by hardware, or can be completed by a program instructing related hardware. The program can be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc.

[0176] The above are only the preferred embodiments of the embodiments of the present application, and are not intended to limit the embodiments of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the embodiments of the present application shall be included in the protection scope of the present application.

Claims

1. A simulation method for driving range, characterized in that The method includes: Obtaining a simulation model of the overall vehicle endurance mileage of an electric vehicle and the energy recovery parameters of the electric vehicle, where the simulation model of the overall vehicle endurance mileage is used to simulate the endurance mileage of the battery of the electric vehicle; Based on the energy recovery parameters of the electric vehicle, determining multiple different levels of energy recovery curves of the electric vehicle; Based on the simulation model of the overall vehicle endurance mileage and the multiple different levels of energy recovery curves, simulating the endurance mileage of the electric vehicle, The simulating the endurance mileage of the electric vehicle based on the simulation model of the overall vehicle endurance mileage and the multiple different levels of energy recovery curves includes: When the electric vehicle is in the overall vehicle matching design stage, based on the simulation model of the overall vehicle endurance mileage and the multiple different levels of energy recovery curves, performing endurance mileage simulations at different levels within a specified range of the state of charge (SOC) of the battery of the electric vehicle to obtain a first simulation result, where the first simulation result includes the maximum endurance mileage corresponding to the energy recovery curve of the maximum level and the distribution of the motor operating points of the electric vehicle; When the maximum endurance mileage does not meet the target endurance mileage, updating the simulation model of the overall vehicle endurance mileage according to the maximum endurance mileage and the distribution of the motor operating points, and returning to the operation of simulating the endurance mileage of the electric vehicle based on the simulation model of the overall vehicle endurance mileage and the multiple different levels of energy recovery curves until the maximum endurance mileage meets the target endurance mileage.

2. The method according to claim 1, characterized in that, The energy recovery parameters include at least one of the maximum recovery ability of the motor of the electric vehicle, the overall vehicle driving experience data, and the braking requirements of the cycle condition; The determining multiple different levels of energy recovery curves of the electric vehicle based on the energy recovery parameters of the electric vehicle includes: When the energy recovery parameters include the overall vehicle driving experience data, determining multiple different levels of energy recovery curves of the electric vehicle based on the maximum recovery ability of the motor, the overall vehicle driving experience data, and the braking requirements of the cycle condition; When the energy recovery parameters do not include the overall vehicle driving experience data, determining the energy recovery curve of the maximum level of the electric vehicle based on the maximum recovery ability of the motor and the braking requirements of the cycle condition; Determining the multiple different levels of energy recovery curves according to multiple different scale factors and the energy recovery curve of the maximum level.

3. The method according to claim 1, wherein The simulating the endurance mileage of the electric vehicle based on the simulation model of the overall vehicle endurance mileage and the multiple different levels of energy recovery curves includes: When the electric vehicle is in the overall vehicle calibration stage, obtaining energy adjustment parameters; According to the energy adjustment parameters, updating the multiple different levels of energy recovery curves; Based on the updated energy recovery curves and the simulation model of the overall vehicle endurance mileage, simulating the endurance mileage of the electric vehicle under the target cycle condition.

4. The method according to claim 1 or 3, characterized in that Before simulating the driving range of the electric vehicle based on the vehicle driving range simulation model and the multiple different levels of energy recovery curves, the following steps are further included: When the electric vehicle is in the vehicle calibration stage, obtain the driving experiment data of the electric vehicle; Calibrate the vehicle driving range simulation model according to the driving experiment data; When the second simulation result of the vehicle driving range simulation model meets the calibration requirements, perform the operation of simulating the driving range of the electric vehicle based on the vehicle driving range simulation model and the multiple different levels of energy recovery curves.

5. The method according to claim 4, characterized in that, After calibrating the vehicle driving range simulation model according to the driving experiment data, the following steps are further included: When the second simulation result does not meet the calibration requirements, update the vehicle driving range simulation model, and return to the operation of calibrating the vehicle driving range simulation model according to the driving experiment data until the second simulation result meets the calibration requirements.

6. A simulation device for cruising range, characterized in that, The device includes: A first acquisition module, configured to acquire a vehicle driving range simulation model of an electric vehicle and the energy recovery parameters of the electric vehicle, where the vehicle driving range simulation model is used to simulate the driving range of the battery of the electric vehicle; A determination module, configured to determine multiple different levels of energy recovery curves of the electric vehicle based on the energy recovery parameters of the electric vehicle; A simulation module, configured to simulate the driving range of the electric vehicle based on the vehicle driving range simulation model and the multiple different levels of energy recovery curves, The simulation module is configured to: When the electric vehicle is in the vehicle matching design stage, perform driving range simulations at different levels within a specified range of the battery SOC of the electric vehicle based on the vehicle driving range simulation model and the multiple different levels of energy recovery curves, to obtain a first simulation result, where the first simulation result includes the maximum driving range corresponding to the energy recovery curve of the maximum level and the distribution of the motor operating points of the electric vehicle; When the maximum driving range does not meet the target driving range, update the vehicle driving range simulation model according to the maximum driving range and the distribution of the motor operating points, and return to the operation of simulating the driving range of the electric vehicle based on the vehicle driving range simulation model and the multiple different levels of energy recovery curves until the maximum driving range meets the target driving range.

7. The device according to claim 6, characterized in that, The energy recovery parameters include at least one of the maximum recovery capacity of the motor of the electric vehicle, the vehicle driving experience data, and the braking requirements of the cycle condition; The determination module is configured to: When the energy recovery parameters include the vehicle driving experience data, determine multiple different levels of energy recovery curves of the electric vehicle based on the maximum recovery capacity of the motor, the vehicle driving experience data, and the braking requirements of the cycle condition; When the vehicle driving experience data is not included in the energy recovery parameters, based on the maximum recovery capacity of the motor and the braking requirements of the driving cycle, determine the energy recovery curve of the maximum level of the electric vehicle; According to a plurality of different proportionality coefficients and the energy recovery curve of the maximum level, determine the energy recovery curves of the plurality of different levels.

8. A computer-readable storage medium, characterized in that, Instructions are stored on the computer-readable storage medium, and when the instructions are executed by a processor, the steps of the method described in any one of claims 1 to 5 above are implemented.

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