A vehicle range calculation method and system

Abstract

The application discloses a kind of whole vehicle endurance mileage calculation method and system, belong to automobile technical field, including following steps: S1: real-time acquisition vehicle operation original parameter;S2: based on power battery parameter, calibration battery real-time available residual energy;S3: calculate driving energy consumption, calculate static accessory energy consumption, calculate dynamic working condition loss energy consumption, obtain whole vehicle real-time unit mileage total energy consumption;S4: to real-time unit mileage total energy consumption is compensated correction, obtain the accurate unit mileage energy consumption after correction;S5: based on battery real-time available residual energy and the accurate unit mileage energy consumption after correction, calculate initial residual endurance mileage;S6: to initial residual endurance mileage is dynamically calibrated, exports final real-time effective endurance mileage.The application breaks through the limitation of traditional fixed power consumption measurement, improves endurance measurement accuracy from the root, and greatly reduces the measurement error.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to a method and system for calculating the driving range of a vehicle. Background Technology

[0002] The current range calculation system for pure electric vehicles is one of the core functions of the vehicle's electronic control system. Its accuracy directly affects users' travel planning, driving experience, and the rationality of the vehicle's electronic control strategy. Currently, most electric vehicle range calculation solutions on the market suffer from low accuracy and poor dynamic adaptability, making it difficult to meet the calculation needs of complex driving scenarios.

[0003] Current mainstream range calculation methods mostly use a fixed average algorithm, which divides the battery's rated total capacity by the vehicle's factory-specified average energy consumption to obtain the theoretical range, or simply adjusts the energy consumption parameters based on short-term driving data. This type of algorithm has several drawbacks: First, it does not consider the battery's degradation characteristics, temperature characteristics, and differences in charge / discharge states, resulting in a significant deviation between the actual usable battery capacity and the rated capacity, with calculation errors being particularly pronounced under low-temperature and older battery conditions. Second, it ignores dynamic changes in driving conditions; factors such as vehicle speed fluctuations, frequent start-stop cycles, hill starts, and the power consumption of air conditioning and onboard electrical appliances can change the vehicle's energy consumption in real time, making fixed energy consumption parameters unsuitable for complex road conditions and driving habits. Third, it lacks a multi-dimensional error compensation mechanism; the static calculation mode cannot adapt to differentiated scenarios such as urban congestion, highway cruising, and mountain roads, commonly resulting in "false range" and "range jumps," which can mislead users' travel plans or even lead to safety hazards such as vehicles running out of power and becoming stranded.

[0004] Existing improvement solutions attempt to incorporate road conditions or temperature parameters to adjust range, but these methods rely on single-dimensional parameters and rigid correction logic. They fail to achieve multi-dimensional fusion calculations considering battery status, driving conditions, environmental parameters, and driving behavior, and cannot dynamically iterate and adjust the model based on real-time vehicle driving data. Consequently, their calculation accuracy is limited, and their adaptive capabilities are poor. Therefore, there is an urgent need for a high-precision, dynamic, and multi-dimensionally adaptable method for calculating electric vehicle range, addressing the issues of low accuracy, poor adaptability, and insufficient stability in existing technologies. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for calculating the driving range of a vehicle, enabling accurate and dynamic calculation of the driving range of an electric vehicle, adapting to all driving conditions, eliminating problems such as falsely advertised or fluctuating driving range, and improving the stability and accuracy of driving range calculation.

[0006] In a first aspect, the present invention describes a method for calculating the driving range of a vehicle, including: S1: Real-time collection of raw vehicle operating parameters, including power battery parameters, vehicle driving parameters, environmental operating condition parameters, and on-board electrical equipment parameters; S2: Based on the power battery parameters, calibrate the real-time available remaining energy Q of the battery; S3: Calculate the driving energy consumption E1 based on the vehicle driving parameters, calculate the static accessory energy consumption E2 based on the on-board electrical equipment parameters, calculate the dynamic operating condition loss energy consumption E3 based on the vehicle driving parameters and the environmental operating condition parameters, and add the driving energy consumption E1, the static accessory energy consumption E2 and the dynamic operating condition loss energy consumption E3 to obtain the total real-time energy consumption per unit mileage of the vehicle E_total. S4: Compensate and correct the real-time total energy consumption per unit mileage E_total to obtain the corrected accurate energy consumption per unit mileage E_correct. S5: Based on the real-time available remaining energy Q of the battery and the corrected precise energy consumption per unit mileage Erep, calculate the initial remaining driving range L0 = Q / Erep; S6: Perform dynamic calibration on the initial remaining driving range L0, and output the final real-time effective driving range L.

[0007] Preferably, the power battery parameters include the battery's real-time open-circuit voltage, remaining SOC value, battery temperature, and battery cycle count; The vehicle driving parameters include real-time vehicle speed, driving acceleration, road conditions, start-stop frequency, and driving gradient; The environmental operating parameters include ambient temperature and wind speed; The parameters of the vehicle-mounted electrical equipment include the real-time power consumption of the air conditioner, headlights, in-vehicle audio-visual equipment, and charging equipment.

[0008] Preferably, step S2 specifically includes the following steps: Retrieve the open-circuit voltage-capacity reference curve calibrated at the battery's factory, obtain the corresponding temperature correction factor based on the battery temperature, and obtain the corresponding aging degradation factor based on the battery cycle count; perform translation calibration on the reference curve based on the temperature correction factor and the aging degradation factor, and obtain the real-time available remaining energy Q by combining the collected real-time open-circuit voltage and remaining SOC value of the battery.

[0009] Preferably, step S3 specifically includes the following steps: The driving energy consumption E1 during vehicle operation is calculated based on real-time vehicle speed, driving acceleration, road conditions, and driving gradient. Based on the parameters of the vehicle-mounted electrical equipment, the energy consumption per unit mileage of the fixed accessories of the whole vehicle is calculated, and the static accessory energy consumption E2 is obtained. Calculate the dynamic operating condition energy loss E3 during the driving process based on ambient temperature, wind speed, and start-stop frequency. Calculate the total energy consumption per unit mileage of the whole vehicle in real time, E_total = E1 + E2 + E3.

[0010] Preferably, the dynamic operating condition energy loss E3 specifically includes: Battery discharge efficiency loss, wind resistance energy loss, instantaneous power loss during start-stop, and potential energy loss when driving on slopes.

[0011] Preferably, step S4 specifically includes: Driving behavior characteristics are obtained from driving data, and corresponding driving behavior correction coefficients are obtained based on these characteristics; operating condition correction coefficients are obtained based on the current road conditions. The corrected precise energy consumption per unit mileage, Ecorrected, is obtained based on the real-time total energy consumption per unit mileage, Etotal, the operating condition correction coefficient, and the driving behavior correction coefficient.

[0012] Preferably, the step of obtaining driving behavior characteristics based on driving data and obtaining corresponding driving behavior correction coefficients based on the driving behavior characteristics specifically includes: Based on the driver's throttle opening of the vehicle within a unit of time, the cumulative throttle fluctuation score of the vehicle within a unit of time is obtained, and the driving behavior correction coefficient is obtained by looking up the table based on the cumulative throttle fluctuation score.

[0013] Preferably, the current road condition is determined based on the current vehicle speed, the severity level corresponding to the current road condition is obtained, and the working condition correction coefficient is obtained by looking up a table based on the severity level.

[0014] Preferably, step S6 specifically includes the following steps: After the vehicle has traveled a preset mileage or a preset interval, the original parameters, driving behavior correction coefficient, and operating condition correction coefficient are updated, and abnormal data caused by instantaneous rapid acceleration and / or short-term high load are removed, and the final real-time effective driving range L is output.

[0015] Secondly, the present invention describes a vehicle range calculation system, comprising: The data acquisition module is used to collect raw parameters of vehicle operation in real time, including power battery parameters, vehicle driving parameters, environmental condition parameters, and on-board electrical equipment parameters. A battery calibration module is used to calibrate the real-time available remaining energy Q of the battery based on the power battery parameters. The total energy consumption calculation module is used to calculate the driving energy consumption E1 based on the vehicle driving parameters, the static accessory energy consumption E2 based on the on-board electrical equipment parameters, and the dynamic operating condition loss energy consumption E3 based on the vehicle driving parameters and the environmental operating condition parameters. The driving energy consumption E1, the static accessory energy consumption E2, and the dynamic operating condition loss energy consumption E3 are added together to obtain the real-time total energy consumption per unit mileage of the vehicle, E_total. The correction module is used to compensate and correct the real-time total energy consumption per unit mileage E_total, so as to obtain the corrected accurate energy consumption per unit mileage E_correct. The module for calculating the initial remaining driving range is used to calculate the initial remaining driving range L0 = Q / E_reduction based on the real-time available remaining energy Q of the battery and the corrected precise energy consumption per unit mile E_reduction. The dynamic calibration module is used to dynamically calibrate the initial remaining driving range L0 and output the final real-time effective driving range L.

[0016] Compared with the prior art, the present invention has the following advantages: 1. This invention adopts a multi-dimensional parameter fusion calculation mode, which breaks through the limitations of traditional fixed power consumption calculation. It fully covers the core parameters that affect the range, such as battery status, driving conditions, environmental factors, electrical load, and driving behavior. It achieves accurate statistics of the vehicle's energy consumption through layered energy consumption (E1, E2, E3) calculation, thereby improving the accuracy of range calculation from the root and significantly reducing calculation errors.

[0017] 2. This invention introduces a dynamic battery calibration mechanism, which combines battery temperature and aging degradation characteristics to correct available power, solves the problem of distortion in range calculation under low temperature and battery aging scenarios, and adapts to the entire life cycle of battery usage.

[0018] 3. This invention sets up a multi-dimensional dynamic correction model that can adapt to all scenarios such as urban congestion, highway cruising, mountain slopes, low and high temperatures, and at the same time match the user's driving habits for personalized correction, and calculate the actual driving conditions, thus completely improving the defects of traditional solutions such as falsely advertised range and data jumps.

[0019] 4. This invention adopts a high-frequency dynamic iterative optimization mechanism to update model parameters and range data in real time, ensuring the smoothness and real-time performance of range display, providing users with accurate travel references, and assisting the vehicle's electronic control system in optimizing energy distribution strategies to improve vehicle range utilization. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a flowchart of one embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0023] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0024] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0025] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0026] Example 1 refer to Figure 1 As shown, the present invention provides a method for calculating the driving range of a vehicle, comprising: S1. Real-time collection of multi-dimensional raw parameters of vehicle operation, including power battery parameters, vehicle driving parameters, environmental condition parameters, and on-board electrical equipment parameters; wherein, the power battery parameters include real-time open-circuit voltage, remaining SOC value, battery temperature, and battery cycle count; the vehicle driving parameters include real-time vehicle speed, driving acceleration, driving road conditions, start-stop frequency, and driving gradient; the environmental condition parameters include ambient temperature and wind speed; and the on-board electrical equipment parameters include real-time power consumption of air conditioning, headlights, in-vehicle audio-visual equipment, and charging equipment.

[0027] S2. Based on the collected power battery parameters, calibrate the real-time available remaining energy Q of the battery: retrieve the pre-established reference curve corresponding to the battery open-circuit voltage-capacity, and dynamically calibrate the reference curve in combination with the remaining SOC value, battery temperature, and battery cycle number to obtain the real-time available remaining energy Q of the power battery. Step S2 can effectively eliminate the power quantity calculation errors caused by battery static loss, temperature loss, and aging loss.

[0028] S3. Calculate the real-time energy consumption per unit mileage of the entire vehicle in a layered manner, breaking down the vehicle's energy consumption into three layers: drive energy consumption, static accessory energy consumption, and dynamic operating condition loss energy consumption. Drive energy consumption E1 is the energy consumption per unit distance of power drive during vehicle operation, calculated based on real-time vehicle speed, acceleration, road friction coefficient, and driving gradient. Static accessory energy consumption E2 is the energy consumption per unit mileage of fixed accessories of the whole vehicle, calculated based on the real-time power consumption of each on-board electrical equipment. The dynamic operating condition energy consumption E3 is the energy consumption per unit mileage during the driving process, calculated based on ambient temperature, wind speed, and start-stop frequency. The total real-time energy consumption per unit mileage of the whole vehicle, Etotal, is calculated as E1 + E2 + E3.

[0029] S4. Construct a multi-dimensional dynamic correction model. The correction model compensates and corrects the total energy consumption per unit mileage through the working condition correction coefficient and the driving behavior correction coefficient, so as to obtain the corrected accurate energy consumption per unit mileage E_correction.

[0030] S5. Based on the real-time available remaining energy Q of the battery and the corrected energy consumption per unit mileage Erep, calculate the initial remaining driving range L0 = Q / Erep.

[0031] S6. Dynamic Iterative Optimization of Range Data: Real-time collection of energy consumption change data during vehicle driving, updating multi-dimensional original parameters and iteratively correcting the model's correction coefficients for each preset mileage or preset interval, dynamically calibrating the initial remaining range L0, outputting the final real-time effective range L and synchronously pushing it to the vehicle display terminal.

[0032] Further, step S2 specifically involves: retrieving the OCV-Q open-circuit voltage-capacity reference curve calibrated at the battery factory, matching a temperature correction factor based on the current battery temperature, matching an aging degradation factor based on the battery cycle count, shifting and calibrating the reference curve, and combining the collected real-time open-circuit voltage and remaining SOC value of the battery to accurately locate the current remaining usable capacity of the battery and calculate the real-time usable remaining energy Q. This effectively avoids the deviation in power calculation caused by low-temperature power loss and battery aging.

[0033] Furthermore, in step S3, the dynamic operating condition energy consumption E3 needs to calculate the following losses: battery discharge efficiency loss under low temperature environment, wind resistance energy consumption loss during high-speed driving, instantaneous power loss during frequent start-stop, and potential energy loss during hill driving, so as to achieve full coverage statistics of energy consumption in all scenarios.

[0034] Furthermore, the method for obtaining each correction coefficient in step S4 is as follows: a parameter matching database is established through big data training. The database pre-stores the correction coefficient ranges for different driving behavior characteristics and road conditions. The current driving behavior characteristics and road conditions are matched in real time to obtain the corresponding optimal correction coefficients. Moreover, the correction coefficients can be automatically iterated and updated based on vehicle driving data.

[0035] Furthermore, in step S6, the preset mileage is set to 1-3km and the preset interval time is set to 5-10s to achieve short-cycle, high-frequency range calibration, avoid large jumps in range, and ensure smooth and stable displayed data.

[0036] Example 2 This embodiment is a specific implementation process of the method for calculating the driving range of a vehicle.

[0037] The first step is real-time parameter acquisition: Vehicle operating parameters are acquired in real time through the vehicle controller, battery management system, environmental sensors, and vehicle speed sensors, including the remaining SOC value of the battery, battery temperature T, open circuit voltage U, battery cycle number n, real-time vehicle speed V, driving acceleration a, driving gradient S, ambient temperature t, wind speed v, and real-time power consumption p of on-board equipment such as air conditioning and headlights. The sampling frequency is set to 10Hz.

[0038] The second step is battery available energy calibration: The vehicle's factory-preset OCV-Q baseline curve is used to calculate the real-time available remaining energy Q of the power battery based on the current open-circuit voltage U and the remaining SOC value.

[0039] Based on the current battery temperature T, the temperature correction factor θ is obtained by referring to the table. The design of the temperature correction factor θ should fully consider the impact of the actual cell performance. The specific value should be determined through calibration to prevent over-compensation and under-compensation. The calibration table of the temperature correction factor θ is shown in Table 1, with the horizontal axis being the battery temperature T.

[0040] Table 1 Temperature Correction Factor Calibration Table

[0041] All data in the table above are calibration values ​​and can be adjusted according to vehicle parameters and actual driving performance. For operating conditions not shown in the table, linear interpolation is used for calculation.

[0042] Based on the current battery cycle number n, the aging correction factor α is obtained by looking up the table. The specific value of the aging correction factor α should be determined by aging test calibration. The calibration table of the aging correction factor α is shown in Table 2, with the cycle number n on the horizontal axis.

[0043] Table 2. Calibration table of aging correction factor

[0044] The third step is layered energy consumption calculation. The overall vehicle energy consumption E is broken down into three parts: driving energy consumption, static accessory energy consumption, and dynamic operating condition loss energy consumption.

[0045] Drive energy consumption: Based on the vehicle's real-time speed V, driving acceleration a, driving slope S, three parameters ABC of the vehicle's sliding resistance curve, and the vehicle's mass M, calculate the energy consumption per unit distance of the vehicle's power drive during the driving process.

[0046] Static accessory energy consumption E2: Based on the real-time power consumption p of on-board equipment such as air conditioning and headlights, the energy consumption of fixed accessories of the whole vehicle per mile is calculated. Dynamic operating condition energy loss E3: Calculate the dynamic operating condition energy loss during vehicle operation based on ambient temperature t and wind speed v.

[0047] The fourth step is multi-coefficient correction. Calculate the correction coefficient β for urban congestion conditions and the correction coefficient γ for mild driving behavior to obtain E-correction.

[0048] Based on the current vehicle speed within a preset time, the severity level x of the current congestion condition is determined. The urban congestion correction coefficient β is obtained by looking up a table based on the severity level x. The urban congestion coefficient β should be obtained through calibration of a large amount of real vehicle data. The calibration table can be shown in the table below, with the horizontal axis representing the severity level x of the congestion condition.

[0049] Table 3. Congestion Coefficient Correspondence Table

[0050] Based on the driver's throttle opening in the vehicle recently, the cumulative throttle fluctuation integral y of the vehicle per unit time is determined. The mild driving behavior correction coefficient γ is obtained by looking up the table based on the cumulative throttle fluctuation integral y. The mild driving behavior correction coefficient γ should be obtained through comprehensive analysis of the big data platform. The corresponding table is shown in Table 4, and its horizontal axis is the cumulative throttle fluctuation integral y.

[0051] Table 4. Correspondence Table of Correction Factors

[0052] The revised formula for calculating E is:

[0053] Step 5, Initial Range Calculation: Calculate the initial remaining range L0 according to the formula.

[0054]

[0055] Step 6, Dynamic Iterative Optimization: Update the original parameters and the correction coefficients of the model once every unit of mileage l or unit of time s, calibrate the range data in real time, eliminate abnormal data caused by instantaneous rapid acceleration and short-term high load, and smoothly output the final real-time range L.

[0056] This invention aims to address the shortcomings of current electric vehicle range calculation solutions, such as low accuracy and poor dynamic adaptability. It adopts a multi-dimensional parameter fusion calculation mode, breaking through the limitations of traditional fixed energy consumption calculation. It fully covers core parameters affecting range, such as battery status, driving conditions, environmental factors, electrical load, and driving behavior. Through layered energy consumption calculation, it achieves accurate statistics of vehicle energy consumption, fundamentally improving the accuracy of range calculation and significantly reducing calculation errors. A dynamic battery calibration mechanism is introduced, which combines battery temperature and aging degradation characteristics to correct available power, solving the problem of range calculation distortion in low temperature and battery aging scenarios, and adapting to the entire life cycle of battery usage. A multi-dimensional dynamic correction model is set up to adapt to all scenarios such as urban congestion, highway cruising, mountain slopes, low temperature and high temperature, while matching the user's driving habits for personalized correction, calculating the range to fit the actual driving conditions, and completely improving the defects of traditional solutions such as false range claims and data jumps. A high-frequency dynamic iterative optimization mechanism is adopted to update model parameters and range data in real time, ensuring the smoothness and real-time nature of range display, providing users with accurate travel references, and assisting the vehicle's electronic control system in optimizing energy distribution strategies to improve vehicle range utilization.

[0057] Finally, it should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems or apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and relevant parts can be referred to the method section.

[0058] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating the driving range of a vehicle, characterized in that, Includes the following steps: S1: Real-time collection of raw vehicle operating parameters, including power battery parameters, vehicle driving parameters, environmental operating condition parameters, and on-board electrical equipment parameters; S2: Based on the power battery parameters, calibrate the real-time available remaining energy Q of the battery; S3: Calculate the driving energy consumption E1 based on the vehicle driving parameters, calculate the static accessory energy consumption E2 based on the on-board electrical equipment parameters, calculate the dynamic operating condition loss energy consumption E3 based on the vehicle driving parameters and the environmental operating condition parameters, and add the driving energy consumption E1, the static accessory energy consumption E2 and the dynamic operating condition loss energy consumption E3 to obtain the total real-time energy consumption per unit mileage of the vehicle E_total. S4: Compensate and correct the real-time total energy consumption per unit mileage E_total to obtain the corrected accurate energy consumption per unit mileage E_correct. S5: Based on the real-time available remaining energy Q of the battery and the corrected precise energy consumption per unit mileage Erep, calculate the initial remaining driving range L0 = Q / Erep; S6: Perform dynamic calibration on the initial remaining driving range L0, and output the final real-time effective driving range L.

2. The method for calculating the driving range of a vehicle according to claim 1, characterized in that, The power battery parameters include the battery's real-time open-circuit voltage, remaining SOC value, battery temperature, and battery cycle count. The vehicle driving parameters include real-time vehicle speed, driving acceleration, road conditions, start-stop frequency, and driving gradient; The environmental operating parameters include ambient temperature and wind speed; The parameters of the vehicle-mounted electrical equipment include the real-time power consumption of the air conditioner, headlights, in-vehicle audio-visual equipment, and charging equipment.

3. The method for calculating the driving range of a vehicle according to claim 2, characterized in that, Step S2 specifically includes the following steps: Retrieve the open-circuit voltage-capacity reference curve calibrated at the battery's factory, obtain the corresponding temperature correction factor based on the battery temperature, and obtain the corresponding aging degradation factor based on the battery cycle count; perform translation calibration on the reference curve based on the temperature correction factor and the aging degradation factor, and obtain the real-time available remaining energy Q by combining the collected real-time open-circuit voltage and remaining SOC value of the battery.

4. The method for calculating the driving range of a vehicle according to claim 2, characterized in that, Step S3 specifically includes the following steps: The driving energy consumption E1 during vehicle operation is calculated based on real-time vehicle speed, driving acceleration, road conditions, and driving gradient. Based on the parameters of the vehicle-mounted electrical equipment, the energy consumption per unit mileage of the fixed accessories of the whole vehicle is calculated, and the static accessory energy consumption E2 is obtained. Calculate the dynamic operating condition energy loss E3 during the driving process based on ambient temperature, wind speed, and start-stop frequency. Calculate the total energy consumption per unit mileage of the whole vehicle in real time, E_total = E1 + E2 + E3.

5. The method for calculating the driving range of a vehicle according to claim 4, characterized in that, The dynamic operating condition energy loss E3 specifically includes: Battery discharge efficiency loss, wind resistance energy loss, instantaneous power loss during start-stop, and potential energy loss when driving on slopes.

6. The method for calculating the driving range of a vehicle according to claim 2, characterized in that, Step S4 specifically includes: Driving behavior characteristics are obtained from driving data, and corresponding driving behavior correction coefficients are obtained based on these characteristics; operating condition correction coefficients are obtained based on the current road conditions. The corrected precise energy consumption per unit mileage, Ecorrected, is obtained based on the real-time total energy consumption per unit mileage, Etotal, the operating condition correction coefficient, and the driving behavior correction coefficient.

7. The method for calculating the driving range of a vehicle according to claim 6, characterized in that, The process of obtaining driving behavior characteristics based on driving data and acquiring corresponding driving behavior correction coefficients based on these characteristics specifically includes: Based on the driver's throttle opening of the vehicle within a unit of time, the cumulative throttle fluctuation score of the vehicle within a unit of time is obtained, and the driving behavior correction coefficient is obtained by looking up the table based on the cumulative throttle fluctuation score.

8. The method for calculating the driving range of a vehicle according to claim 6, characterized in that, The operating condition correction factor is obtained based on the current road conditions, specifically including: The current road condition is determined based on the current vehicle speed, the severity level corresponding to the current road condition is obtained, and the working condition correction coefficient is obtained by looking up the table based on the severity level.

9. The method for calculating the driving range of a vehicle according to claim 6, characterized in that, Step S6 specifically includes the following steps: After the vehicle has traveled a preset mileage or a preset interval, the original parameters, driving behavior correction coefficient, and operating condition correction coefficient are updated, and abnormal data caused by instantaneous rapid acceleration and / or short-term high load are removed, and the final real-time effective driving range L is output.

10. A vehicle range calculation system, characterized in that, include: The data acquisition module is used to collect raw parameters of vehicle operation in real time, including power battery parameters, vehicle driving parameters, environmental condition parameters, and on-board electrical equipment parameters. A battery calibration module is used to calibrate the real-time available remaining energy Q of the battery based on the power battery parameters. The total energy consumption calculation module is used to calculate the driving energy consumption E1 based on the vehicle driving parameters, the static accessory energy consumption E2 based on the on-board electrical equipment parameters, and the dynamic operating condition loss energy consumption E3 based on the vehicle driving parameters and the environmental operating condition parameters. The driving energy consumption E1, the static accessory energy consumption E2, and the dynamic operating condition loss energy consumption E3 are added together to obtain the real-time total energy consumption per unit mileage of the vehicle, E_total. The correction module is used to compensate and correct the real-time total energy consumption per unit mileage E_total, so as to obtain the corrected accurate energy consumption per unit mileage E_correct. The module for calculating the initial remaining driving range is used to calculate the initial remaining driving range L0 = Q / E_reduction based on the real-time available remaining energy Q of the battery and the corrected precise energy consumption per unit mile E_reduction. The dynamic calibration module is used to dynamically calibrate the initial remaining driving range L0 and output the final real-time effective driving range L.

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