Low-consumption continuous cruising evaluation method and device, electronic equipment, medium and product

Abstract

The application discloses a low-consumption and endurance-maintaining evaluation method and device, electronic equipment, medium and product. The method comprises the following steps: acquiring navigation information and whole-vehicle state information of a vehicle; performing energy consumption prediction according to the navigation information and the whole-vehicle state information to obtain current average energy consumption and minimum reachable energy consumption; performing endurance evaluation according to the whole-vehicle state information, the current average energy consumption and the minimum reachable energy consumption to obtain an endurance evaluation result; when it is determined according to the endurance evaluation result that the low-consumption and endurance-maintaining mode needs to be started, outputting a low-consumption and endurance-maintaining mode starting prompt information; and when receiving confirmation information fed back by a user in response to the low-consumption and endurance-maintaining mode starting prompt information, controlling the vehicle to start the low-consumption and endurance-maintaining mode. The method can solve the problem that potential endurance risks cannot be identified in the early stage of a journey, thereby leading to unreliable vehicle endurance prediction.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, specifically to a low-consumption range assessment method, device, electronic device, readable storage medium, and computer program product. Background Technology

[0002] With the increasing popularity of electric vehicles, range anxiety remains a key factor affecting user experience, especially in complex scenarios such as long journeys and extreme temperatures. Actual vehicle energy consumption surges due to road conditions, environmental factors, and air conditioning usage, leading to inaccurate range predictions. Existing technologies primarily rely on a single range calculation model based on historical average energy consumption, which cannot accurately predict future energy consumption changes and risks during the journey. In practice, existing methods fail to identify potential range risks early in the journey, often only providing reactive warnings when the battery is significantly low. Users lack sufficient time and optimization space to adjust driving and energy usage habits to ensure arrival at their destination, reducing the reliability of vehicle range prediction. Summary of the Invention

[0003] In view of the above problems, this application provides a low-consumption range assessment method, apparatus, electronic device, readable storage medium and computer program product, which can solve the problem that potential range risks cannot be identified in the early stages of a journey, resulting in unreliable vehicle range prediction.

[0004] Firstly, this application provides a low-power, long-lasting battery life assessment method, including: Obtain vehicle navigation information and overall vehicle status information; Based on the navigation information and the vehicle status information, energy consumption is predicted to obtain the current average energy consumption and the minimum achievable energy consumption. Based on the vehicle status information, the current average energy consumption, and the minimum achievable energy consumption, a range assessment is performed to obtain a range assessment result. When it is determined from the battery life assessment results that the low power consumption protection mode needs to be activated, a low power consumption protection mode activation prompt message is output. Upon receiving confirmation from the user regarding the activation of the low-consumption, extended-range mode, the system controls the vehicle to activate the low-consumption, extended-range mode.

[0005] In the aforementioned technical solution, this method provides comprehensive and accurate basic data support for subsequent energy consumption prediction and range assessment based on navigation information and vehicle status information. Simultaneously, predicting the current average energy consumption and minimum achievable energy consumption based on navigation and vehicle status information overcomes the limitations of traditional single historical average energy consumption models, thus providing a quantitative basis for range risk assessment. Then, conducting a range assessment based on vehicle status information, current average energy consumption, and minimum achievable energy consumption accurately identifies potential range risks early in the journey, transforming passive battery warnings into proactive risk prediction, thereby allowing users sufficient adjustment time. Next, based on the range assessment results, a low-energy-consumption range-preserving mode activation prompt is output, ensuring the assessment results are intuitively fed back to the user, protecting their right to know and their decision-making rights. Finally, based on the received user confirmation, the method controls the vehicle to activate the low-energy-consumption range-preserving mode, transforming the assessment conclusions into practical energy-saving interventions, thereby optimizing vehicle energy consumption output, effectively improving the reliability of range prediction and the range achievement rate, and helping the vehicle smoothly reach its destination.

[0006] In some embodiments, after the vehicle is controlled to activate the low-consumption, extended-range mode, the method further includes: Calculate the range anxiety level based on the navigation information, the vehicle status information, and the current average energy consumption; Based on the stated range anxiety and the navigation information, determine the vehicle speed dynamic limit threshold; Based on the preset thermal management parameters, the navigation information, and the range anxiety, the target power limit value of the thermal management system is calculated; wherein, the preset thermal management parameters include at least the thermal management power limit value for non-low power consumption range mode and the rated thermal management power. Based on preset energy recovery parameters and the vehicle status information, a target energy management strategy is determined; wherein, the energy recovery parameters include at least battery recovery capacity, total power of high-voltage accessories, motor recovery capacity, and basic braking recovery power; In the low-consumption range protection mode, the vehicle speed is limited according to the vehicle speed dynamic limit threshold, the vehicle's thermal management system power is limited according to the target power limit value, and the vehicle's energy recovery torque control command is generated according to the target energy management strategy.

[0007] In the above technical solution, the method can dynamically set the vehicle speed limit threshold by calculating the range stress and combining it with navigation information after the low-consumption range protection mode is activated. At the same time, it can accurately adjust the power of the thermal management system based on preset thermal management parameters and range stress, and formulate a target energy management strategy by combining energy recovery parameters and vehicle status information. Finally, it can achieve refined energy consumption control from three dimensions: vehicle speed control, thermal management power limitation, and energy recovery torque adjustment, thereby further reducing vehicle energy consumption, improving range protection capability, and ensuring that the vehicle can reach its destination smoothly even in complex scenarios.

[0008] In some implementations, calculating the range anxiety based on the navigation information, the vehicle status information, and the current average energy consumption includes: Obtain the navigation distance based on the navigation information; The remaining battery power is obtained based on the vehicle status information; The range anxiety is calculated based on the navigation distance, the remaining battery power, and the current average energy consumption.

[0009] In the above technical solution, the method can accurately calculate the range stress based on three core quantitative indicators: navigation distance, remaining battery power, and current average energy consumption. This provides an objective and quantifiable basis for decision-making regarding dynamic speed limits, thermal management system power regulation, and energy recovery strategies in low-consumption range-preserving mode. It avoids control deviations caused by subjective judgment and further improves the accuracy of energy consumption control and the reliability of range assurance.

[0010] In some implementations, determining the dynamic speed limit threshold based on the range anxiety and the navigation information includes: Obtain the legal speed limit for the road based on the navigation information; The recommended speed is calculated based on the preset optimal energy efficiency speed, the preset battery impact coefficient, and the range anxiety level. The dynamic speed limit threshold is determined based on the legal speed limit for the road and the recommended speed.

[0011] In the above technical solution, the method can combine the legal speed limit of the road in the navigation information, as well as the preset optimal energy efficiency speed, the power impact coefficient and the range pressure to calculate the recommended speed. Then, the dynamic speed limit threshold is determined by the dual constraints of the legal speed limit and the recommended speed. While ensuring the compliance of vehicle driving, it can also dynamically optimize the speed according to the range pressure to reduce energy consumption, achieving a balance between compliance and energy saving, and further improving the accuracy of energy consumption control in the low-consumption range-preserving mode.

[0012] In some implementations, calculating the target power limit value of the thermal management system based on preset thermal management parameters, the navigation information, and the range anxiety includes: The current ambient temperature is obtained based on the navigation information; Determine the temperature influence coefficient based on the current ambient temperature; The base power limit value is calculated based on the stated range stress, preset thermal management parameters, and temperature influence coefficient. The maximum power limit is determined based on the base power limit and the thermal management power limit for the non-low power consumption extended battery life mode. When the vehicle's motor or battery has thermal management requirements, the maximum power limit value is determined as the target power limit value; When there is no thermal management requirement for the vehicle's motor or battery, the base power limit value is determined as the target power limit value.

[0013] In the above technical solution, the method can dynamically adjust the power of the thermal management system by combining ambient temperature and range stress, taking into account the basic thermal management needs of core components and energy-saving goals, so as to achieve refined control of thermal management energy consumption and improve the energy-saving effect of low-consumption range-preserving mode.

[0014] In some implementations, determining the target energy management strategy based on preset energy recovery parameters and the vehicle status information includes: The current motor efficiency is obtained based on the vehicle status information; Determine the compensation coefficient based on the current motor efficiency; Calculate the maximum recovery power of the entire vehicle based on the battery recovery capacity, the total power of the high-voltage accessories, the compensation coefficient, and the motor recovery capacity. The compensated regenerative braking power is calculated based on the basic regenerative braking power, the maximum regenerative braking power of the vehicle, the total power of the high-voltage accessories, and the compensation coefficient. Calculate the requested regenerative braking power based on the base regenerative braking power, the maximum regenerative braking power of the vehicle, and the compensated regenerative braking power; The current energy management strategy is optimized based on the requested power recovery to obtain the target energy management strategy.

[0015] In the above technical solution, the method can combine motor efficiency and various energy recovery parameters to accurately calculate the recoverable power of the whole vehicle, optimize the energy management strategy, maximize the energy recovery utilization rate, further reduce the energy consumption of the whole vehicle, and improve the range guarantee capability.

[0016] In some implementations, the step of predicting energy consumption based on the navigation information and the vehicle status information to obtain the current average energy consumption and the minimum achievable energy consumption includes: Based on the navigation information, obtain traffic congestion level, road slope information, and current weather information; Calculate the road condition coefficient based on the traffic congestion level and the preset road condition weighting factor; The average slope is calculated based on the road slope information, and the slope coefficient is calculated based on the average slope. Determine the weather coefficient based on the current weather information; Energy consumption is predicted based on the preset baseline energy consumption, the road condition coefficient, the slope coefficient, and the weather coefficient to obtain the current average energy consumption; The minimum achievable energy consumption is calculated based on preset vehicle parameters, current weather information, slope coefficient, and weather coefficient.

[0017] In the above technical solution, the method can integrate multiple dimensions of actual driving influencing factors such as road conditions, slope, and weather to construct a multi-coefficient coupled energy consumption prediction model, accurately calculate the current average energy consumption and the minimum achievable energy consumption, and provide a scientific and quantitative basis for energy consumption range for subsequent range assessment.

[0018] In some implementations, calculating the minimum achievable energy consumption based on preset vehicle parameters, the current weather information, the slope coefficient, and the weather coefficient includes: Obtain preset vehicle parameters; wherein the preset vehicle parameters include at least minimum accessory energy consumption, optimal energy efficiency speed, transmission system efficiency, rolling resistance coefficient, vehicle mass, and frontal area; Based on the current weather information, obtain the air density and drag coefficient; The rolling resistance energy consumption is calculated based on the rolling resistance coefficient, the vehicle mass, and the transmission system efficiency. Calculate drag energy consumption based on the frontal area, air density, drag coefficient, optimal energy efficiency speed, and transmission system efficiency; Calculate the slope coefficient based on the road slope information, and determine the weather coefficient based on the current weather information; The minimum achievable energy consumption is calculated based on the minimum accessory energy consumption, the rolling resistance energy consumption, the wind resistance energy consumption, the slope coefficient, and the weather coefficient.

[0019] In the above technical solution, the method can break down and accurately calculate the energy consumption components such as rolling resistance and wind resistance based on the vehicle's basic parameters, weather and slope, thereby quantifying the minimum achievable energy consumption of the vehicle under ideal working conditions, defining the energy-saving potential boundary for range assessment and improving the accuracy of energy consumption prediction.

[0020] In some implementations, the step of evaluating the driving range based on the vehicle status information, the current average energy consumption, and the minimum achievable energy consumption to obtain the driving range evaluation result includes: The remaining battery power is obtained based on the vehicle status information; Calculate the current energy consumption reachable distance based on the remaining battery power and the current average energy consumption, and calculate the minimum energy consumption reachable distance based on the remaining battery power and the minimum reachable energy consumption; The navigation distance is obtained based on the navigation information, and a distance threshold is calculated based on the navigation distance and a preset redundancy distance; When the current energy consumption reachable distance is less than the navigation distance, and the minimum energy consumption reachable distance is greater than or equal to the distance threshold, the battery life assessment result is determined to be that the low energy consumption battery life protection mode needs to be enabled, and the step of outputting the low energy consumption battery life protection mode enable prompt information is executed.

[0021] In the above technical solution, the method can accurately identify the range risk in the early stage of the journey by quantifying the current energy consumption achievable distance and the minimum energy consumption achievable distance, and make a dual judgment by combining navigation distance and redundancy distance thresholds, clarify the conditions for activating the low energy consumption range protection mode, and provide reliable decision support for proactive energy-saving intervention.

[0022] In some implementations, the method further includes: When the minimum energy consumption reachable distance is less than the distance threshold, the battery life assessment result is determined to be a charging warning required, and the power consumption corresponding to the minimum energy consumption is calculated based on the distance threshold and the minimum reachable energy consumption. Calculate the charging capacity based on the power consumption corresponding to the minimum energy consumption and the remaining battery capacity; The output includes charging warning information including the charging level.

[0023] In the above technical solution, the method can promptly trigger a charging warning when it is determined that the minimum energy consumption achievable distance is still insufficient to meet the travel needs, and accurately calculate the required charging power. It visualizes and quantifies the warning information, helps users plan their charging schemes in advance, and avoids the predicament of travel interruption due to insufficient battery life.

[0024] Secondly, this application provides a low-power consumption and long-term battery life evaluation device, comprising: The acquisition unit is used to acquire the vehicle's navigation information and overall vehicle status information; An energy consumption prediction unit is used to predict energy consumption based on the navigation information and the vehicle status information to obtain the current average energy consumption and the minimum achievable energy consumption. The range assessment unit is used to assess the range based on the vehicle status information, the current average energy consumption, and the minimum achievable energy consumption, and to obtain the range assessment result. The output unit outputs a low-power battery protection mode activation prompt message when it is determined from the battery life assessment result that the low-power battery protection mode needs to be activated. The control unit is used to control the vehicle to activate the low-consumption and long-range protection mode when it receives confirmation from the user regarding the activation prompt message of the low-consumption and long-range protection mode.

[0025] In the aforementioned technical solution, the device provides comprehensive and accurate basic data support for subsequent energy consumption prediction and range assessment based on navigation information and vehicle status information. Simultaneously, it predicts the current average energy consumption and minimum achievable energy consumption based on navigation and vehicle status information, overcoming the limitations of traditional single historical average energy consumption models and providing a quantitative basis for range risk assessment. Then, based on vehicle status information, current average energy consumption, and minimum achievable energy consumption, a range assessment is conducted, accurately identifying potential range risks early in the journey and transforming passive battery warnings into proactive risk prediction, thus allowing users sufficient adjustment time. Next, based on the range assessment results, a low-energy-consumption range-preserving mode activation prompt is output, ensuring the assessment results are intuitively fed back to the user, protecting their right to know and make decisions. Finally, based on the received user confirmation, the device controls the vehicle to activate the low-energy-consumption range-preserving mode, transforming the assessment conclusions into practical energy-saving interventions, thereby optimizing vehicle energy consumption output, effectively improving the reliability of range prediction and range achievement rate, and helping the vehicle smoothly reach its destination.

[0026] Thirdly, this application provides an electronic device, the electronic device including a memory and a processor, the memory for storing a computer program, the processor running the computer program to cause the electronic device to perform the low power consumption and battery life assessment method described in any one of the first aspects.

[0027] Fourthly, this application provides a readable storage medium storing a computer program, which, when executed by a processor, performs the low-power consumption and long-lasting battery life evaluation method described in any one of the first aspects.

[0028] Fifthly, this application provides a computer program product, which includes a computer program that, when run by a processor, executes the low-power consumption and long-lasting battery life evaluation method described in any one of the first aspects.

[0029] The beneficial effects of this application are as follows: it can greatly improve the accuracy of range estimation by using multi-factor fusion energy consumption prediction; it can also systematically perform drive coordination, thermal management and energy recovery, thereby effectively reducing energy consumption; it can also provide early warning and clear solutions to effectively alleviate range anxiety; and it can also optimize energy consumption while ensuring thermal management safety, avoiding battery over-discharge or overheating. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart illustrating the low-power consumption and extended battery life evaluation method in some embodiments of this application; Figure 2 This is a system architecture diagram showing the application of the low-power consumption and long-lasting battery life evaluation method in some embodiments of this application; Figure 3 This is a flowchart illustrating the low-power consumption and extended battery life evaluation method in some embodiments of this application; Figure 4 This is a schematic diagram of the low power consumption and long battery life evaluation device in some embodiments of this application; Figure 5 This is a schematic diagram of the structure of an electronic device in some embodiments of this application. Detailed Implementation

[0032] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0033] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0034] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more (including two), similarly, "multiple sets" refers to two or more sets (including two sets), and "multiple pieces" refers to two or more pieces (including two pieces) unless otherwise explicitly defined.

[0035] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0036] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0037] With the increasing popularity of electric vehicles, range anxiety remains a key factor affecting user experience, especially in complex scenarios such as long journeys and extreme temperatures. Actual vehicle energy consumption surges due to road conditions, environmental factors, and air conditioning usage, leading to inaccurate range predictions. Existing technologies primarily rely on a single range calculation model based on historical average energy consumption, which cannot accurately predict future energy consumption changes and risks during the journey. In practice, existing methods fail to identify potential range risks early in the journey, often only providing reactive warnings when the battery is significantly low. Users lack sufficient time and optimization space to adjust driving and energy usage habits to ensure arrival at their destination, reducing the reliability of vehicle range prediction.

[0038] To address the aforementioned technical issues, this application provides a low-energy-consumption range assessment method. This method can intelligently reduce vehicle energy consumption by predicting range risks in advance and dynamically coordinating the motor, thermal management system, and energy recovery system, while ensuring the vehicle reaches its destination. Therefore, this method is more suitable for demanding conditions such as long-distance travel, extreme temperatures, or battery aging.

[0039] like Figure 1 As shown, some embodiments of this application provide a low-power consumption and battery life assessment method, which includes: S101. Obtain the vehicle's navigation information and overall vehicle status information; S102. Based on navigation information and vehicle status information, predict energy consumption to obtain the current average energy consumption and the minimum achievable energy consumption; S103. Based on the vehicle status information, current average energy consumption, and minimum achievable energy consumption, conduct a range assessment to obtain the range assessment result. S104. When it is determined from the battery life assessment results that the low power consumption and battery life protection mode needs to be activated, output a prompt message indicating that the low power consumption and battery life protection mode needs to be activated. S105. Upon receiving confirmation from the user regarding the activation of the low-consumption and extended-range mode, control the vehicle to activate the low-consumption and extended-range mode.

[0040] In some embodiments, navigation information refers to data related to the vehicle's planned route, including at least navigation distance, legal speed limits, traffic congestion levels, road gradient information, and current weather information.

[0041] In some embodiments, vehicle status information refers to various status parameters during vehicle operation, including at least data related to energy consumption and range such as remaining battery power, current motor efficiency, and vehicle component operating conditions.

[0042] In some embodiments, the current average energy consumption refers to the average energy consumption per unit mileage predicted by combining navigation information and vehicle status information under the current driving conditions and environmental conditions.

[0043] In some embodiments, minimum achievable energy consumption refers to the minimum energy consumption that a vehicle can achieve per unit mileage under ideal energy-saving conditions, calculated based on factors such as vehicle parameters, road conditions, and weather.

[0044] In some embodiments, the range assessment result refers to the conclusion drawn after assessing whether the vehicle's remaining battery power can support the completion of the planned trip based on the vehicle status information, the current average energy consumption, and the minimum achievable energy consumption. This includes whether it is necessary to activate the low-energy-consumption range protection mode and whether it is necessary to issue a charging warning.

[0045] In some embodiments, the low-consumption extended-range mode refers to an energy-saving operating mode activated by the vehicle to reduce energy consumption and extend the driving range. Energy consumption optimization can be achieved by adjusting vehicle speed, thermal management system power, energy recovery strategies, and other means.

[0046] In some embodiments, the low-power battery life mode activation prompt message refers to a notification message pushed to the user to prompt the user to confirm the activation of the low-power battery life mode when the battery life assessment determines that the low-power battery life mode needs to be activated.

[0047] In some embodiments, when the vehicle arrives at its destination, or the driver manually turns it off, or charging is detected to have started, the system automatically exits the low-consumption range protection mode, resumes normal driving mode, and generates an energy-saving report to show the energy-saving results of the trip.

[0048] In some embodiments, after controlling the vehicle to activate the low-consumption range-saving mode, the method further includes: When the vehicle is detected to have reached its destination, or when a user inputs a command to exit the low-consumption range protection mode, or when the vehicle is detected to have started charging, the system controls the vehicle to exit the low-consumption range protection mode.

[0049] In the above embodiments, this method can provide comprehensive and accurate basic data support for subsequent energy consumption prediction and range assessment based on navigation information and vehicle status information. Simultaneously, predicting the current average energy consumption and minimum achievable energy consumption based on navigation information and vehicle status information overcomes the limitations of traditional single historical average energy consumption models, thus providing a quantitative basis for range risk assessment. Then, conducting a range assessment based on vehicle status information, current average energy consumption, and minimum achievable energy consumption allows for accurate identification of potential range risks early in the journey, transforming passive battery warnings into proactive risk prediction, thereby providing users with sufficient adjustment time. Next, based on the range assessment results, a low-energy-consumption range-preserving mode activation prompt is output, ensuring that the assessment results are intuitively fed back to the user, protecting the user's right to know and decision-making. Finally, based on the received user confirmation information, the method controls the vehicle to activate the low-energy-consumption range-preserving mode, transforming the assessment conclusions into practical energy-saving intervention measures, thereby optimizing vehicle energy consumption output, effectively improving the reliability of range prediction and range achievement rate, and helping the vehicle smoothly reach its destination.

[0050] In some embodiments, after controlling the vehicle to activate the low-consumption range-preserving mode, the method further includes: Calculate the range anxiety level based on navigation information, vehicle status information, and current average energy consumption; Determine the dynamic speed limit threshold based on range anxiety and navigation information; Based on preset thermal management parameters, navigation information, and range anxiety, the target power limit value of the thermal management system is calculated; wherein, the preset thermal management parameters include at least the thermal management power limit value of the non-low power consumption range mode and the rated thermal management power. Based on preset energy recovery parameters and vehicle status information, a target energy management strategy is determined; among which, the energy recovery parameters include at least the battery recovery capacity, the total power of high-voltage accessories, the motor recovery capacity, and the basic braking recovery power; In the low-consumption range protection mode, the vehicle speed is limited according to the vehicle speed dynamic limit threshold, the power of the vehicle's thermal management system is limited according to the target power limit value, and the energy recovery torque control command of the vehicle is generated according to the target energy management strategy.

[0051] In the above embodiments, after the low-consumption range-preserving mode is activated, the method can dynamically set the vehicle speed limit threshold by calculating the range stress and combining it with navigation information. At the same time, it can accurately adjust the power of the thermal management system based on preset thermal management parameters and range stress, and formulate a target energy management strategy by combining energy recovery parameters and vehicle status information. Finally, it can achieve refined energy consumption control from three dimensions: vehicle speed control, thermal management power limitation, and energy recovery torque adjustment, further reducing vehicle energy consumption, improving range assurance capability, and ensuring that the vehicle can reach its destination smoothly even in complex scenarios.

[0052] In some embodiments, the range anxiety is calculated based on navigation information, vehicle status information, and current average energy consumption, including: Obtain the navigation distance based on navigation information; The remaining battery power is obtained based on the vehicle status information; Calculate range anxiety based on navigation distance, remaining battery power, and current average energy consumption.

[0053] In some embodiments, the formula for calculating range anxiety is as follows: D_ratio=(D_nav×E_current) / SOE; Wherein, D_ratio is the range stress level, which is a quantitative indicator used to characterize the pressure on the vehicle's remaining battery power to support the current range of the journey; D_nav is the navigation distance, which refers to the total mileage of the vehicle's planned journey; E_current is the current average energy consumption, which refers to the average energy consumption per unit mileage of the vehicle under the current operating conditions and environment; SOE stands for Remaining Battery Energy, which refers to the total output electrical energy currently remaining in the vehicle's battery.

[0054] In the above embodiments, the method can accurately calculate the range anxiety based on three core quantitative indicators: navigation distance, remaining battery power, and current average energy consumption. This provides an objective and quantifiable basis for decision-making regarding vehicle speed dynamic limits, thermal management system power regulation, and energy recovery strategies in low-consumption range protection mode. It avoids control deviations caused by subjective judgment and further improves the accuracy of energy consumption control and the reliability of range protection.

[0055] In some embodiments, determining a dynamic speed limit threshold based on range anxiety and navigation information includes: Obtain the legal speed limit for the road based on navigation information; The recommended speed is calculated based on the preset optimal energy efficiency speed, the preset battery impact coefficient, and the range pressure. The dynamic speed limit threshold is determined based on the legal speed limit and recommended speed for roads.

[0056] In some embodiments, the formula for calculating the vehicle speed dynamic limit threshold is as follows: v_max=min(v_legal,v_efficient); v_efficient=v_opt×[1+K_soc×(1 D_ratio)]; Among them, v_max refers to the dynamic speed limit threshold, which is the maximum driving speed allowed for the vehicle in the low-consumption range mode. min() is a function that retrieves the minimum value; v_legal is the legal speed limit for the road, referring to the legal maximum speed for the current road segment; v_efficient is the recommended speed for energy efficiency, which refers to the optimal energy-saving speed calculated in combination with the range anxiety level; v_opt is the energy-efficient optimal speed, which refers to the speed at which the vehicle travels under ideal conditions with the lowest energy consumption. K_soc is the SOC influence coefficient, which is a coefficient that decreases as the remaining battery capacity (SOC) decreases. D_ratio represents the battery life stress level; 1 D_ratio: Range pressure adjustment item, used to dynamically adjust the recommended vehicle speed.

[0057] In some embodiments, the core of the motor system control strategy is to ensure that the motor always operates in the most efficient range, while reasonably limiting the vehicle speed to reduce wind resistance energy consumption.

[0058] In some embodiments, based on the motor efficiency MAP, the control formula that ensures the motor torque output meets driving requirements while remaining within the region of peak efficiency ≥90% is as follows: T_opt=f_efficiency_map(ω,η_target); P_motor_limit=min(P_request,T_opt×ω); Where T_opt is the optimal torque (unit: N) (m) refers to the optimal output torque of the motor in its high-efficiency range under the current operating conditions; f_efficiency_map() is a motor efficiency MAP mapping function. This function matches the torque value with the optimal motor efficiency based on the input parameters. ω represents the motor speed, referring to the current operating speed of the motor; η_target is the target efficiency value (≥90%), which refers to the set peak efficiency threshold of the motor; P_motor_limit is the motor power limit value, which refers to the maximum allowable output power of the motor; P_reques represents the motor's power demand, which refers to the motor output power requested by the driver / vehicle controller during vehicle operation.

[0059] In the above embodiments, the method can combine the legal speed limit of the road in the navigation information with the preset optimal energy efficiency speed, the power impact coefficient and the range pressure to calculate the recommended speed. Then, the dynamic speed limit threshold is determined by the dual constraints of the legal speed limit and the recommended speed. While ensuring the compliance of vehicle driving, it can also dynamically optimize the speed according to the range pressure to reduce energy consumption, achieving a balance between compliance and energy saving, and further improving the accuracy of energy consumption control in the low-consumption range-preserving mode.

[0060] In some embodiments, the target power limit value of the thermal management system is calculated based on preset thermal management parameters, navigation information, and range anxiety, including: Obtain the current ambient temperature based on navigation information; Determine the temperature influence coefficient based on the current ambient temperature; The base power limit is calculated based on the range stress, preset thermal management parameters, and temperature influence coefficient. The maximum power limit is determined based on the base power limit and the thermal management power limit for non-low power consumption extended driving mode. When the vehicle's motor or battery has thermal management requirements, the maximum power limit value is determined as the target power limit value; When there is no thermal management requirement for the vehicle's motor or battery, the base power limit value is determined as the target power limit value.

[0061] In some embodiments, the thermal management system is the second largest energy consumer in an electric vehicle after the drive motor, accounting for up to 54.1% of the total energy consumption in low-temperature environments. Therefore, it is necessary to adaptively limit the power of the thermal management system based on the ambient temperature and range anxiety.

[0062] In some embodiments, the base power limit value is calculated using the following formula: P_ac_base=Min(P_ac_norm×K_temp×min(1,1 / D_ratio),P_ac_Limit); Among them, P_ac_Limit is the thermal management power limit value in non-battery protection mode, which is the basic power limit of the thermal management system calculated in combination with ambient temperature and range stress. P_ac_norm is the rated thermal management power, which refers to the rated operating power of the thermal management system. K_temp is the temperature influence coefficient, which refers to the correction coefficient calibrated based on the current ambient temperature (specific calibration depends on the actual vehicle); K_temp = 1.0 (T_out < 0°C or T_out > 30°C); K_temp = 0.7 (15°C ≤ T_out ≤ 25°C); K_temp = 0.85 (other temperatures); D_ratio represents the battery life stress level; P_ac_Limit is the power limit value for thermal management in non-navigation mode, which refers to the upper limit of the thermal management system power of the vehicle in normal mode.

[0063] In this embodiment, since the motor and battery of a pure electric vehicle are greatly affected by temperature, which directly affects the efficiency and safety of the motor and battery, the maintenance mode needs to prioritize the thermal management requirements.

[0064] For example, if the motor or battery has thermal management requirements (heating or cooling), the thermal management power limit needs to be relaxed, and the maximum value of the base power limit P_ac_base and the thermal management power limit P_ac_Limit for non-low power consumption protection mode should be taken. Specifically, the target power limit P_ac is determined by the following formula: P_ac=max(P_ac_base,P_ac_Limit).

[0065] In the above embodiments, the method can dynamically adjust the power of the thermal management system by combining ambient temperature and range anxiety, taking into account both the basic thermal management needs of core components and energy-saving goals, thereby achieving refined control of thermal management energy consumption and improving the energy-saving effect of the low-consumption range-preserving mode.

[0066] In some embodiments, a target energy management strategy is determined based on preset energy recovery parameters and vehicle status information, including: Obtain the current motor efficiency based on the vehicle status information; Determine the compensation coefficient based on the current motor efficiency; Calculate the maximum recovery power of the entire vehicle based on the battery recovery capacity, the total power of the high-voltage accessories, the compensation coefficient, and the motor recovery capacity; The compensated regenerative braking power is calculated based on the basic regenerative braking power, the maximum regenerative braking power of the vehicle, the total power of the high-voltage accessories, and the compensation coefficient. Calculate the requested regenerative braking power based on the base regenerative braking power, the maximum regenerative braking power of the vehicle, and the compensated regenerative braking power; The current energy management strategy is optimized based on the requested power recovery to obtain the target energy management strategy.

[0067] In some embodiments, the formula for calculating the maximum recycling capacity of the entire vehicle is as follows: P_regen_max=min((P_regen_bat+P_aux_total)×K_comp,P_regen_mot) The formula is explained as follows: Maximum vehicle recycling capacity = min((battery recycling capacity + high voltage accessory power) * compensation coefficient, motor recycling capacity).

[0068] In some embodiments, the formula for calculating the requested power recovery is as follows: P_regen_req=min(P_regen_max,P_regen_base+P_aux_comp); The formula is explained as follows: Requested recovery power = min(vehicle maximum recovery capacity, basic braking / coasting recovery power + compensation recovery power).

[0069] In some embodiments, the formula for calculating the compensated power recovery is as follows: P_aux_comp=min(P_aux_total,P_regen_max-P_regen_base)×K_comp; The formula is explained as follows: Compensation recovery power = min(power of high-voltage accessories, maximum recovery capacity of the whole vehicle - basic braking / coasting recovery power) * compensation coefficient.

[0070] In some embodiments, P_regen_max is the maximum regenerated power of the entire vehicle; P_regen_req is the requested power to be regenerated; P_regen_bat represents the battery recycling capability; P_regen_mot represents the motor recycling capability; P_regen_base is the base braking / coasting regeneration power; P_aux_total represents the total power of the high-voltage accessories; P_aux_comp represents the compensation power for power recovery. K_comp is the compensation coefficient, which is adjusted based on motor efficiency deviation. In some embodiments, the compensation coefficient K_comp is determined according to the following rules: High-efficiency region (η≥90%): K_comp=1.05; Mid-range region (80%≤η<90%): K_comp=1.12; Inefficient region (η<80%): K_comp=1.25.

[0071] In some embodiments, the regenerative torque capability and verification are based on the above energy management strategy and interact normally with the ESP.

[0072] In the above embodiments, the method can combine motor efficiency and various energy recovery parameters to accurately calculate the recoverable power of the whole vehicle, optimize energy management strategy, maximize energy recovery utilization rate, further reduce vehicle energy consumption, and improve range assurance capability.

[0073] In some embodiments, energy consumption prediction is performed based on navigation information and vehicle status information to obtain the current average energy consumption and the minimum achievable energy consumption, including: Obtain traffic congestion levels, road gradient information, and current weather information based on navigation information; The road condition coefficient is calculated based on the degree of traffic congestion and the preset road condition weighting factor. Calculate the average slope based on the road slope information, and then calculate the slope coefficient based on the average slope. Determine the weather coefficient based on current weather information; Based on preset baseline energy consumption, road condition coefficient, slope coefficient, and weather coefficient, energy consumption is predicted to obtain the current average energy consumption; The minimum achievable energy consumption is calculated based on preset vehicle parameters, current weather information, slope coefficient, and weather coefficient.

[0074] In some embodiments, the formula for predicting the current average energy consumption is: E_current=E_base×K_road×K_slope×K_weather; Among them, E_base is the basic energy consumption; K_road is the road condition coefficient, K_road=1.2×(proportion of expressway sections)+0.9×(proportion of urban road sections)+1.25×(proportion of congested road sections); K_slope is the slope coefficient, K_slope=1+0.05×|average slope%|; K_weather is the weather coefficient (sunny day = 1.0, rainy day = 1.1, snowy day = 1.3).

[0075] In some embodiments, the specific coefficients are adjusted based on the actual vehicle.

[0076] In the above embodiments, the method can integrate multiple dimensions of actual driving influencing factors such as road conditions, slope, and weather to construct a multi-coefficient coupled energy consumption prediction model, accurately calculate the current average energy consumption and the minimum achievable energy consumption, and provide a scientific and quantitative basis for subsequent range assessment.

[0077] In some embodiments, the minimum achievable energy consumption is calculated based on preset vehicle parameters, current weather information, gradient coefficient, and weather coefficient, including: Obtain preset vehicle parameters; wherein the preset vehicle parameters include at least minimum accessory energy consumption, optimal energy efficiency speed, transmission system efficiency, rolling resistance coefficient, vehicle mass, and frontal area; Obtain air density and drag coefficient based on current weather information; Calculate rolling resistance energy consumption based on rolling resistance coefficient, vehicle mass, and transmission system efficiency; Calculate drag energy consumption based on frontal area, air density, drag coefficient, optimal energy efficiency speed, and transmission system efficiency. Calculate the slope coefficient based on road gradient information, and determine the weather coefficient based on current weather information; The minimum achievable energy consumption is calculated based on the minimum attachment energy consumption, rolling resistance energy consumption, wind resistance energy consumption, slope coefficient, and weather coefficient.

[0078] In some embodiments, the minimum energy consumption model takes into account the vehicle's theoretical minimum energy consumption value, and its calculation method is as follows: E_min = (E_roll + E_aero + E_aux_min) × K_slope × K_weather / / Energy consumption to overcome resistance has already taken vehicle speed into account, so the operating condition coefficient is not considered; E_roll=μ×m×g×v_opt / (3600×η_drv) / / rolling resistance energy consumption; E_aero=0.5×ρ×A×C_d×v_opt 3 / (3600×η_drv×1000) / / Wind resistance energy consumption; E_min is the minimum achievable energy consumption, which refers to the minimum energy consumption per unit mileage of a vehicle under ideal energy-saving operating conditions. E_roll represents rolling resistance energy consumption, which refers to the energy consumed by the vehicle to overcome the rolling resistance of the tires during driving. E_aero is wind resistance energy consumption, which refers to the energy consumption generated by the vehicle overcoming air resistance while driving; E_aux_min is the minimum accessory energy consumption, which refers to the minimum energy consumption required for the vehicle accessory system to maintain basic operation; K_slope is the slope coefficient, which refers to the energy consumption correction coefficient calculated based on the average slope of the road. K_weather is the weather coefficient, an energy consumption correction factor calibrated based on the current weather (sunny / rainy / snowy); μ is the rolling resistance coefficient, which is a parameter that characterizes the magnitude of rolling resistance between the tire and the road surface; m represents the vehicle mass (in kg), which is the sum of the vehicle's curb weight and its payload. g is the acceleration due to gravity (default value is 9.8 m / s²). 2 ); v_opt is the energy-efficient optimal speed, which refers to the ideal driving speed with the lowest energy consumption of the vehicle; η_drv is the transmission system efficiency, which refers to the energy transmission efficiency of the vehicle transmission system (value 0~1). 3600 is the unit conversion factor (converting hours to seconds, km / h to m / s); ρ is the air density (unit: kg / m³) 3 (Air density value that varies with ambient temperature and altitude); A is the windward area (unit: m²). 2 ), the projected area of ​​the vehicle's front perpendicular to the direction of travel; C_d is the drag coefficient, a parameter that characterizes the aerodynamic characteristics of a vehicle (the smaller the value, the lower the drag). v_opt 3 It is the cube of the optimal energy-efficiency vehicle speed (wind resistance energy consumption is proportional to the cube of the vehicle speed). 1000 is the unit conversion factor (converting joules to kilojoules, and finally to kWh).

[0079] In the above embodiments, the method can break down and accurately calculate the energy consumption components such as rolling resistance and wind resistance based on vehicle basic parameters, weather and slope, thereby quantifying the minimum achievable energy consumption of the vehicle under ideal working conditions, defining the energy-saving potential boundary for range assessment, and improving the accuracy of energy consumption prediction.

[0080] In some embodiments, a range assessment is performed based on vehicle status information, current average energy consumption, and minimum achievable energy consumption to obtain a range assessment result, including: The remaining battery power is obtained based on the vehicle status information; Calculate the current energy consumption reachable distance based on the remaining battery power and the current average energy consumption, and calculate the minimum energy consumption reachable distance based on the remaining battery power and the minimum reachable energy consumption. The navigation distance is obtained based on the navigation information, and a distance threshold is calculated based on the navigation distance and a preset redundancy distance. When the current energy consumption reachable distance is less than the navigation distance, and the minimum energy consumption reachable distance is greater than or equal to the distance threshold, the battery life assessment result is determined to be that the low energy consumption battery life protection mode needs to be turned on, and the step of outputting the low energy consumption battery life protection mode turn-on prompt message is executed.

[0081] In some embodiments, the formula for calculating the current energy consumption achievable distance is as follows: D_current = SOE / E_current Where D_current is the current energy consumption reachable distance, which refers to the maximum driving range that the remaining battery power can support when driving according to the current average energy consumption; SOE stands for remaining battery capacity (kWh). E_current is the current average energy consumption, which refers to the average energy consumption per unit mileage of the vehicle under the current operating conditions and environment; In some embodiments, the formula for calculating the minimum energy consumption achievable distance is as follows: D_min = SOE / E_min; wherein D_min is the minimum energy consumption reachable distance, which refers to the maximum driving range that the remaining battery capacity can support when the vehicle travels at the minimum achievable energy consumption; SOE is the remaining battery capacity; E_min is the minimum achievable energy consumption, which refers to the minimum energy consumption per unit mileage of the vehicle under ideal energy-saving operating conditions.

[0082] In some embodiments, the trigger condition for the low-consumption range-preserving mode is: when the current energy consumption reachable distance of the vehicle is less than the navigation distance, and the minimum energy consumption reachable distance plus the anti-shake threshold of 10km is greater than or equal to the navigation distance (i.e., D_current<D_nav and D_min+10km≥D_nav).

[0083] wherein D_current is the current energy consumption reachable distance; D_nav is the navigation distance; D_min is the minimum energy consumption reachable distance; 10km is the anti-shake threshold.

[0084] For example, when the low-consumption range-preserving mode is triggered, the in-vehicle system may push a prompt message to the user: "Current energy consumption cannot reach the destination, do you want to enable the range-preserving mode?"; if a confirmation enable instruction fed back by the user is received, the system activates the low-consumption range-preserving mode, and displays a prompt message to the user: "Range-preserving mode is enabled: the vehicle speed may be limited to {v_max}km / h, and the thermal management power may be reduced".

[0085] In the above embodiments, the method can perform dual determination by quantifying the current energy consumption reachable distance and the minimum energy consumption reachable distance, combined with the navigation distance and the redundant distance threshold, accurately identify the range risk in the early stage of the trip, clarify the enabling conditions of the low-consumption range-preserving mode, and provide reliable decision support for active energy-saving intervention.

[0086] In some embodiments, the method further comprises: when the minimum energy consumption reachable distance is less than the distance threshold, determining that the range assessment result is that a charging warning is required, and calculating the consumed electric quantity corresponding to the minimum energy consumption according to the distance threshold and the minimum achievable energy consumption; calculating the required charging electric quantity according to the consumed electric quantity corresponding to the minimum energy consumption and the remaining battery capacity; outputting charging warning information including the required charging electric quantity.

[0087] In some embodiments, if the minimum energy consumption reachable distance D_min is less than the navigation distance D_nav+10km, the system needs to calculate the required charging electric quantity; wherein the calculation formula for the consumed electric quantity E_required corresponding to the minimum energy consumption is: E_required=(D_nav+10)×E_min; The formula for calculating the required charging power (Charge_required) is as follows: Charge_required=E_required-SOE; If Charge_required > 0, the vehicle system will prompt the user for the amount of additional charge required: Charge_required (kWh).

[0088] In some embodiments, if the vehicle's minimum energy consumption achievable distance D_min is less than the sum of the navigation distance D_nav and 10km, that is: If D_min < (D_nav + 10), the system calculates the required charging amount. The formula for calculating the required charging amount is: Required charging amount = max(0, D_nav × E_min - SOC × C_battery). At the same time, the vehicle system pushes a prompt message to the user: "If you still cannot reach the destination by using the lowest energy consumption, it is recommended to charge {required charging amount} kWh".

[0089] In the above embodiments, the method can promptly trigger a charging warning when it is determined that the minimum energy consumption achievable distance is still insufficient to meet the travel requirements, and accurately calculate the required charging power. It visualizes and quantifies the warning information, helps users plan their charging schemes in advance, and avoids the predicament of travel interruption due to insufficient battery life.

[0090] To make the purpose, technical solution and advantages of this application clearer, the technical solution in this application will be clearly and completely described below.

[0091] In some embodiments, such as Figure 2 As shown, the overall system architecture for applying this low-power, long-range evaluation method includes: Traffic information collection module: Real-time acquisition of navigation distance, road gradient, traffic congestion level, and weather information; Energy consumption prediction module: Based on a comprehensive energy consumption prediction model with multiple factors; Battery life assessment module: Dual-mode battery life assessment mechanism; The navigation mode control module includes three sub-modules: vehicle speed limit, thermal management system management, and energy recovery. Human-computer interaction module: provides warnings, suggestions, and status display.

[0092] In some embodiments, such as Figure 3 As shown, the low-consumption, long-lasting battery life assessment method includes: S201, Initialization Phase.

[0093] Get navigation information: distance D_nav, real-time traffic conditions, slope profile, and weather information.

[0094] Read vehicle status: SOC, SOE, current average energy consumption, battery, motor thermal management request.

[0095] S202, Range Risk Assessment.

[0096] Calculate E_current and E_min.

[0097] Evaluate D_current and D_min.

[0098] Determine whether to trigger the protection mode recommendation.

[0099] S203, Navigation Protection Mode Activated.

[0100] After user confirmation, the system enters the navigation protection mode.

[0101] v_max is dynamically set based on D_ratio.

[0102] Adjust P_ac based on temperature and thermal management requirements.

[0103] Optimize energy recovery strategies.

[0104] S204. Real-time monitoring and adjustment.

[0105] Continuously monitor the discrepancy between actual energy consumption and forecasts.

[0106] Adaptively adjust control parameters.

[0107] Provides real-time display of arrival probability.

[0108] Figure 4 A schematic diagram of a low-power, long-lasting battery life evaluation device is shown. It should be understood that this device is related to... Figure 1 The method executed in the middle corresponds to the steps involved in the aforementioned method. The specific functions and effects of the device can be found in the description above. To avoid repetition, detailed descriptions are omitted here.

[0109] The low-power consumption and long-lasting battery life assessment device includes: The acquisition unit 310 is used to acquire the vehicle's navigation information and overall vehicle status information; The energy consumption prediction unit 320 is used to predict energy consumption based on navigation information and vehicle status information to obtain the current average energy consumption and the minimum achievable energy consumption. The range assessment unit 330 is used to assess the range based on the vehicle status information, current average energy consumption, and minimum achievable energy consumption, and obtain the range assessment result. Output unit 340 outputs a low-power battery protection mode activation prompt message when it is determined from the battery life assessment results that the low-power battery protection mode needs to be activated. The control unit 350 is used to control the vehicle to activate the low-consumption and long-range protection mode when it receives confirmation information from the user regarding the prompt message for activating the low-consumption and long-range protection mode.

[0110] In some embodiments, the low-power battery life assessment device further includes: The calculation unit 360 is used to calculate the range stress based on navigation information, vehicle status information and current average energy consumption after the control unit 350 controls the vehicle to start the low energy consumption and range protection mode. The determination unit 370 is used to determine the dynamic speed limit threshold based on the range anxiety and navigation information; The calculation unit 360 is also used to calculate the target power limit value of the thermal management system based on preset thermal management parameters, navigation information, and range anxiety; wherein the preset thermal management parameters include at least the thermal management power limit value of the non-low power consumption range mode and the rated thermal management power. The determining unit 370 is also used to determine the target energy management strategy based on preset energy recovery parameters and vehicle status information; wherein, the energy recovery parameters include at least the battery recovery capacity, the total power of high-voltage accessories, the motor recovery capacity, and the basic braking recovery power; The generation unit 380 is used to limit the vehicle speed according to the vehicle speed dynamic limit threshold, limit the power of the vehicle's thermal management system according to the target power limit value, and generate the vehicle's energy recovery torque control command according to the target energy management strategy in the low-consumption range mode.

[0111] In some embodiments, the computing unit 360 includes: The first acquisition subunit 361 is used to acquire the navigation distance based on navigation information; The first acquisition subunit 361 is also used to acquire the remaining battery power based on the vehicle status information; The first calculation subunit 362 is used to calculate the range stress based on navigation distance, remaining battery power, and current average energy consumption.

[0112] In some embodiments, the determining unit 370 includes: The second acquisition subunit 371 is used to acquire the legal speed limit of the road based on navigation information; The second calculation subunit 372 is used to calculate the recommended speed based on the preset optimal energy efficiency speed, the preset power impact coefficient, and the range pressure. The second determining subunit 373 is used to determine the dynamic speed limit threshold based on the road's legal speed limit and recommended speed.

[0113] In some embodiments, the computing unit 360 includes: The first acquisition subunit 361 is also used to acquire the current ambient temperature based on navigation information; The first determining subunit 363 is used to determine the temperature influence coefficient based on the current ambient temperature; The first calculation subunit 362 is used to calculate the basic power limit value based on the range stress, preset thermal management parameters and temperature influence coefficient; The first determining subunit 363 is also used to determine the maximum power limit value based on the basic power limit value and the thermal management power limit value of the non-low power consumption protection mode; The first determining subunit 363 is also used to determine the maximum power limit value as the target power limit value when the vehicle's motor or battery has thermal management requirements; The first determining subunit 363 is also used to determine the base power limit value as the target power limit value when there is no thermal management requirement for the vehicle's motor or battery.

[0114] In some embodiments, the determining unit 370 includes: The second acquisition subunit 371 is also used to acquire the current motor efficiency based on the vehicle status information; The second determining subunit 373 is also used to determine the compensation coefficient based on the current motor efficiency; The second calculation subunit 372 is also used to calculate the maximum recovery power of the whole vehicle based on the battery recovery capacity, the total power of the high voltage accessories, the compensation coefficient and the motor recovery capacity; The second calculation subunit 372 is also used to calculate the compensation recovery power based on the basic braking recovery power, the maximum recovery power of the whole vehicle, the total power of the high-voltage accessories and the compensation coefficient; The second calculation subunit 372 is also used to calculate the requested recovery power based on the basic braking recovery power, the maximum recovery power of the whole vehicle, and the compensated recovery power; The optimization subunit 374 is used to optimize the current energy management strategy based on the requested power recovery to obtain the target energy management strategy.

[0115] In some embodiments, the energy consumption prediction unit 320 includes: The third acquisition subunit 321 is used to acquire traffic congestion level, road slope information and current weather information based on navigation information; The third calculation subunit 322 is used to calculate the road condition coefficient based on the degree of traffic congestion and the preset road condition weighting factor; The third calculation subunit 322 is also used to calculate the average slope based on the road slope information and to calculate the slope coefficient based on the average slope. The third determining subunit 323 is used to determine the weather coefficient based on the current weather information; The prediction subunit 324 is used to predict energy consumption based on preset basic energy consumption, road condition coefficient, slope coefficient, and weather coefficient to obtain the current average energy consumption. The third calculation subunit 322 is also used to calculate the minimum achievable energy consumption based on preset vehicle parameters, current weather information, slope coefficient and weather coefficient.

[0116] In some embodiments, the third calculation subunit 322 is specifically used to obtain preset vehicle parameters; wherein, the preset vehicle parameters include at least minimum accessory energy consumption, optimal energy-efficient vehicle speed, transmission system efficiency, rolling resistance coefficient, vehicle mass, and frontal area. The third calculation subunit 322 is specifically used to obtain air density and wind resistance coefficient based on current weather information; The third calculation subunit 322 is specifically used to calculate rolling resistance energy consumption based on the rolling resistance coefficient, vehicle mass and transmission system efficiency; The third calculation subunit 322 is specifically used to calculate wind resistance energy consumption based on frontal area, air density, drag coefficient, optimal energy efficiency vehicle speed and transmission system efficiency; The third calculation subunit 322 is also used to calculate the slope coefficient based on the road slope information and determine the weather coefficient based on the current weather information. The third calculation subunit 322 is specifically used to calculate the minimum achievable energy consumption based on the minimum attachment energy consumption, rolling resistance energy consumption, wind resistance energy consumption, slope coefficient, and weather coefficient.

[0117] In some embodiments, the battery life evaluation unit 330 includes: The fourth acquisition subunit 331 is used to acquire the remaining battery power based on the vehicle status information; The fourth calculation subunit 332 is used to calculate the current energy consumption reachable distance based on the remaining battery power and the current average energy consumption, and to calculate the minimum energy consumption reachable distance based on the remaining battery power and the minimum reachable energy consumption. The fourth calculation subunit 332 is also used to obtain the navigation distance based on the navigation information, and to calculate the distance threshold based on the navigation distance and the preset redundancy distance; The fourth determining subunit 333 is used to determine the endurance assessment result as requiring the low-power endurance mode to be enabled when the current energy consumption reachable distance is less than the navigation distance and the minimum energy consumption reachable distance is greater than or equal to the distance threshold, and to execute the step of outputting a low-power endurance mode enable prompt information.

[0118] In some embodiments, the fourth determining subunit 333 is further configured to determine that the battery life assessment result is a charging warning is needed when the minimum energy consumption reachable distance is less than the distance threshold, and to calculate the power consumption corresponding to the minimum energy consumption based on the distance threshold and the minimum reachable energy consumption. The fourth calculation subunit 332 is also used to calculate the charging power based on the power consumption corresponding to the minimum power consumption and the remaining power of the battery; Output subunit 334 is used to output charging warning information including the charging level.

[0119] like Figure 5 As shown, this application provides an electronic device 400, which includes a processor 401 and a memory 402. The processor 401 and the memory 402 are interconnected and communicate with each other through a communication bus 403 and / or other forms of connection mechanism (not shown). The memory 402 stores a computer program that can be executed by the processor 401. When the computing device is running, the processor 401 executes the computer program to perform the method in any of the aforementioned optional implementations.

[0120] This application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the method in any of the aforementioned optional implementations.

[0121] The computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0122] This application provides a computer program product, which includes a computer program that, when run by a processor, executes the method in any of the aforementioned optional implementations.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them. Although this application 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 or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and they should all be covered within the scope of the claims and specification of this application. In particular, as long as there is no conflict, the various technical features mentioned in the embodiments can be combined in any way. This application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method for evaluating low-power consumption and extended battery life, characterized in that, include: Obtain vehicle navigation information and overall vehicle status information; Based on the navigation information and the vehicle status information, energy consumption is predicted to obtain the current average energy consumption and the minimum achievable energy consumption. Based on the vehicle status information, the current average energy consumption, and the minimum achievable energy consumption, a range assessment is performed to obtain a range assessment result. When it is determined from the battery life assessment results that the low power consumption protection mode needs to be activated, a low power consumption protection mode activation prompt message is output. Upon receiving confirmation from the user regarding the activation of the low-consumption and extended-range mode, the system controls the vehicle to activate the low-consumption and extended-range mode. The method further includes, after the vehicle is controlled to activate the low-consumption, extended-range mode: Calculate the range anxiety level based on the navigation information, the vehicle status information, and the current average energy consumption; Based on the stated range anxiety and the navigation information, determine the vehicle speed dynamic limit threshold; Based on the preset thermal management parameters, the navigation information, and the range anxiety, the target power limit value of the thermal management system is calculated; wherein, the preset thermal management parameters include at least the thermal management power limit value for non-low power consumption range mode and the rated thermal management power. Based on preset energy recovery parameters and the vehicle status information, a target energy management strategy is determined; wherein, the energy recovery parameters include at least battery recovery capacity, total power of high-voltage accessories, motor recovery capacity, and basic braking recovery power; In the low-consumption range mode, the vehicle speed is limited according to the vehicle speed dynamic limit threshold, the vehicle's thermal management system power is limited according to the target power limit value, and the vehicle's energy recovery torque control command is generated according to the target energy management strategy. The step of calculating the range anxiety based on the navigation information, the vehicle status information, and the current average energy consumption includes: Obtain the navigation distance based on the navigation information; The remaining battery power is obtained based on the vehicle status information; The range anxiety is calculated based on the navigation distance, the remaining battery power, and the current average energy consumption.

2. The low-power consumption and long-term battery life evaluation method according to claim 1, characterized in that, The step of determining the dynamic speed limit threshold based on the range anxiety and the navigation information includes: Obtain the legal speed limit for the road based on the navigation information; The recommended speed is calculated based on the preset optimal energy efficiency speed, the preset battery impact coefficient, and the range anxiety level. The dynamic speed limit threshold is determined based on the legal speed limit for the road and the recommended speed.

3. The low-power consumption and long-term battery life evaluation method according to claim 1, characterized in that, The step of calculating the target power limit value of the thermal management system based on preset thermal management parameters, navigation information, and range anxiety includes: The current ambient temperature is obtained based on the navigation information; Determine the temperature influence coefficient based on the current ambient temperature; The base power limit value is calculated based on the stated range stress, preset thermal management parameters, and temperature influence coefficient. The maximum power limit is determined based on the base power limit and the thermal management power limit for the non-low power consumption extended battery life mode. When the vehicle's motor or battery has thermal management requirements, the maximum power limit value is determined as the target power limit value; When there is no thermal management requirement for the vehicle's motor or battery, the base power limit value is determined as the target power limit value.

4. The low-power consumption and extended battery life evaluation method according to claim 1, characterized in that, The step of determining the target energy management strategy based on preset energy recovery parameters and the vehicle status information includes: The current motor efficiency is obtained based on the vehicle status information; Determine the compensation coefficient based on the current motor efficiency; Calculate the maximum recovery power of the entire vehicle based on the battery recovery capacity, the total power of the high-voltage accessories, the compensation coefficient, and the motor recovery capacity. The compensated regenerative braking power is calculated based on the basic regenerative braking power, the maximum regenerative braking power of the vehicle, the total power of the high-voltage accessories, and the compensation coefficient. Calculate the requested regenerative braking power based on the base regenerative braking power, the maximum regenerative braking power of the vehicle, and the compensated regenerative braking power; The current energy management strategy is optimized based on the requested power recovery to obtain the target energy management strategy.

5. The low-power consumption and long-term battery life evaluation method according to claim 1, characterized in that, The step of predicting energy consumption based on the navigation information and the vehicle status information to obtain the current average energy consumption and the minimum achievable energy consumption includes: Based on the navigation information, obtain traffic congestion level, road slope information, and current weather information; Calculate the road condition coefficient based on the traffic congestion level and the preset road condition weighting factor; The average slope is calculated based on the road slope information, and the slope coefficient is calculated based on the average slope. Determine the weather coefficient based on the current weather information; Energy consumption is predicted based on the preset baseline energy consumption, the road condition coefficient, the slope coefficient, and the weather coefficient to obtain the current average energy consumption; The minimum achievable energy consumption is calculated based on preset vehicle parameters, current weather information, slope coefficient, and weather coefficient.

6. The low-power consumption and long-term battery life evaluation method according to claim 5, characterized in that, The step of calculating the minimum achievable energy consumption based on preset vehicle parameters, current weather information, slope coefficient, and weather coefficient includes: Obtain preset vehicle parameters; wherein the preset vehicle parameters include at least minimum accessory energy consumption, optimal energy efficiency speed, transmission system efficiency, rolling resistance coefficient, vehicle mass, and frontal area; Based on the current weather information, obtain the air density and drag coefficient; The rolling resistance energy consumption is calculated based on the rolling resistance coefficient, the vehicle mass, and the transmission system efficiency. Calculate drag energy consumption based on the frontal area, air density, drag coefficient, optimal energy efficiency speed, and transmission system efficiency; The slope coefficient is calculated based on the road slope information, and the weather coefficient is determined based on the current weather information; The minimum achievable energy consumption is calculated based on the minimum accessory energy consumption, the rolling resistance energy consumption, the wind resistance energy consumption, the slope coefficient, and the weather coefficient.

7. The low-consumption, long-range evaluation method according to claim 1, characterized in that, The process of evaluating the driving range based on the vehicle status information, the current average energy consumption, and the minimum achievable energy consumption to obtain the driving range evaluation result includes: The remaining battery power is obtained based on the vehicle status information; Calculate the current energy consumption reachable distance based on the remaining battery power and the current average energy consumption, and calculate the minimum energy consumption reachable distance based on the remaining battery power and the minimum reachable energy consumption; The navigation distance is obtained based on the navigation information, and a distance threshold is calculated based on the navigation distance and a preset redundancy distance; When the current energy consumption reachable distance is less than the navigation distance, and the minimum energy consumption reachable distance is greater than or equal to the distance threshold, the battery life assessment result is determined to be that the low energy consumption battery life protection mode needs to be enabled, and the step of outputting the low energy consumption battery life protection mode enable prompt information is executed.

8. The low-consumption, long-term battery life assessment method according to claim 7, characterized in that, The method further includes: When the minimum energy consumption reachable distance is less than the distance threshold, the battery life assessment result is determined to be a charging warning required, and the power consumption corresponding to the minimum energy consumption is calculated based on the distance threshold and the minimum reachable energy consumption. Calculate the charging capacity based on the power consumption corresponding to the minimum energy consumption and the remaining battery capacity; The output includes charging warning information including the charging level.

9. A low-power consumption, long-lasting battery life evaluation device, characterized in that, The low-power consumption and long-lasting battery life evaluation device includes: The acquisition unit is used to acquire the vehicle's navigation information and overall vehicle status information; An energy consumption prediction unit is used to predict energy consumption based on the navigation information and the vehicle status information to obtain the current average energy consumption and the minimum achievable energy consumption. The range assessment unit is used to assess the range based on the vehicle status information, the current average energy consumption, and the minimum achievable energy consumption, and to obtain the range assessment result. The output unit is used to output a low-power battery protection mode activation prompt message when it is determined from the battery life evaluation result that the low-power battery protection mode needs to be activated. The control unit is used to control the vehicle to activate the low-consumption and long-range protection mode when it receives confirmation information from the user regarding the activation prompt information of the low-consumption and long-range protection mode. The low-power consumption and long-lasting battery life assessment device also includes: The calculation unit is used to calculate the range anxiety based on the navigation information, the vehicle status information and the current average energy consumption after the control unit controls the vehicle to start the low-consumption range protection mode; The determining unit is used to determine a dynamic speed limit threshold based on the range anxiety and the navigation information; The calculation unit is also used to calculate the target power limit value of the thermal management system based on the preset thermal management parameters, the navigation information, and the range anxiety; wherein the preset thermal management parameters include at least the thermal management power limit value of the non-low power consumption range mode and the rated thermal management power. The determining unit is further configured to determine a target energy management strategy based on preset energy recovery parameters and the vehicle status information; wherein the energy recovery parameters include at least battery recovery capacity, total power of high-voltage accessories, motor recovery capacity, and basic braking recovery power; The generation unit is used to limit the vehicle speed according to the vehicle speed dynamic limit threshold in the low-consumption range mode, limit the power of the vehicle's thermal management system according to the target power limit value, and generate the vehicle's energy recovery torque control command according to the target energy management strategy. The computing unit includes: The first acquisition subunit is used to acquire the navigation distance based on the navigation information; The first acquisition subunit is further configured to acquire the remaining battery power based on the vehicle status information; The first calculation subunit is used to calculate the range anxiety based on the navigation distance, the remaining battery power, and the current average energy consumption.

10. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory being used to store a computer program, and the processor running the computer program to cause the electronic device to perform the low-power battery life assessment method according to any one of claims 1 to 8.

11. A readable storage medium, characterized in that, The readable storage medium stores a computer program, which, when executed by a processor, performs the low-power consumption and long-lasting battery life evaluation method according to any one of claims 1 to 8.

12. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, performs the low-power consumption and long-lasting battery life evaluation method as described in any one of claims 1 to 8.

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