CN-122008953-A - Whole vehicle energy management and endurance optimization method for low-speed four-wheel electric vehicle

CN122008953ACN 122008953 ACN122008953 ACN 122008953ACN-122008953-A

Abstract

The invention discloses a whole vehicle energy management and endurance optimization method of a low-speed four-wheel electric vehicle, in particular relates to the technical field of electric vehicle energy management, and aims to solve the problems of rough energy distribution and low reliability of finishing key task nodes of the existing low-speed four-wheel electric vehicle. The method comprises the steps of acquiring task information comprising the order of stop points and the importance degree of the tasks before the tasks are started, dividing a guarantee unit, a compressible unit and a sacrificial unit by combining a historical task record, distributing energy budget according to the traction and accessory energy characteristics of each unit under the constraint of available energy and lower limit of charge of a battery, and constructing an energy envelope which is monotonously reduced along with the task, so that the purposes of finely planning battery energy around a task structure on the premise of not increasing hardware cost, preferentially guaranteeing that key stop points are completed according to a plan and exposing risks of insufficient energy in advance are achieved, and the endurance stability and the task completion rate of the low-speed four-wheel electric vehicle under the repetitive scenes such as park commute are improved.

Inventors

LIU YILIN
ZHANG GUANGHUI
CHEN GANG

Assignees

天津豪爵阳光电动车有限公司

Dates

Publication Date: 20260512
Application Date: 20260312

Claims (9)

1. The whole vehicle energy management and endurance optimization method for the low-speed four-wheel electric vehicle is characterized by comprising the following steps of: S1, acquiring task information and historical data, dividing a guarantee unit, a compressible unit and a sacrificial unit, and counting the traction energy and accessory energy characteristics of each task unit; S2, under the constraint of available energy and a lower limit of charge of a battery, distributing traction energy budget and accessory energy budget for each task unit according to energy characteristics and priorities to form an accumulated energy envelope; S3, generating a control parameter set consisting of a traction power upper limit, a regenerative braking torque coefficient and an accessory power limit value for each task unit based on the energy envelope, and sequentially storing the control parameter set into a vehicle controller; S4, periodically collecting traction energy and accessory energy of each task unit in the execution process, calculating actual and budget deviation, and combining the residual energy and the energy budget of the subsequent task unit to obtain the risk index distribution of completion of the subsequent task; S5, obtaining an energy-saving adjustment coefficient according to the energy deviation and the subsequent task completion risk index distribution, and scaling the traction power upper limit, the vehicle speed limit value and the acceleration limit value according to the energy-saving adjustment coefficient, so that the regenerative braking torque coefficient is improved, and the accessory power limit value is reduced; and S6, updating an energy characteristic table, a risk calculation parameter and an energy-saving adjustment coefficient mapping table according to the actual energy of each task unit and the task completion condition when the task is finished, so as to be called when the follow-up energy envelope construction and the control parameter set generation are carried out.
2. The method for whole vehicle energy management and endurance optimization of a low-speed four-wheel electric vehicle according to claim 1, wherein S1 comprises: The vehicle controller is used for calling task information and historical task records, aligning time sequence numbers to the measurement signals according to a sampling rhythm and marking the records exceeding a physical limit range as invalid measurement points; dividing a historical task record into task units according to the stop point sequence and the vehicle door opening and closing state, and dividing the task units into a guarantee unit, a compressible unit and a sacrificial unit according to the task importance degree marks and the task completion condition quantity; And counting traction energy, accessory energy and corresponding power characteristics of various task units, and writing an energy characteristic table according to the task unit types and the task unit sequences.
3. The method for whole vehicle energy management and endurance optimization of a low-speed four-wheel electric vehicle according to claim 1, wherein S2 comprises: the vehicle controller determines available energy of the battery according to the battery charge state quantity, the battery nominal capacity, the charge lower limit and the efficiency reduction coefficient; Reading a traction energy average value and an accessory energy average value from an energy feature table according to the task unit sequence as a traction energy budget initial value and an accessory energy budget initial value, and calculating an initial total energy demand; When the initial total energy demand is greater than the available energy of the battery, setting an accessory energy compression coefficient and a traction energy compression coefficient for the compressible unit and the sacrificial unit, reducing the compression coefficient by compression rounds, and obtaining a final energy budget under the constraint that the traction energy budget and the accessory energy budget of each task unit are not lower than the lower limit of the respective safety energy; the vehicle controller builds an energy envelope curve based on the final energy budget and stores the energy envelope curve and the task session identification in the task parameter area.
4. The method for whole vehicle energy management and endurance optimization of a low-speed four-wheel electric vehicle according to claim 1, wherein S3 comprises: the vehicle controller determines the expected running time of each task unit according to the expected running mileage in the task information and the statistical result of the vehicle speed quantity of each task unit in the energy characteristic table; Dividing the traction energy budget of each task unit by the expected running time to obtain an average traction power boundary, comparing the average traction power boundary with the announcement power of the whole vehicle, the long-term allowable power of the motor and the temperature rise constraint power one by one, and taking the minimum value as the upper limit of the traction power of the task unit; The upper traction power limit and the vehicle speed limit and the acceleration limit matched with the upper traction power limit are written into a control parameter set in a task parameter area.
5. The method for managing and optimizing the whole vehicle energy of the low-speed four-wheel electric vehicle according to claim 4, wherein the vehicle controller determines the energy redundancy of each task unit according to the energy envelope value range, inputs the energy redundancy and the grade of gradient difficulty into a mapping table to select a regenerative braking torque coefficient, and corrects the regenerative braking torque coefficient under the constraint of the upper limit of battery charging current; The vehicle controller divides the vehicle-mounted accessory into a safety-related accessory and a comfort-related accessory according to the task information, determines the upper limit of the average total power of the accessory system according to the energy budget and the expected duration of the accessory, and determines the power limit of the safety-related accessory and the power limit of the comfort-related accessory according to the priority principle of the safety-related accessory; And associating the traction power upper limit, the regenerative braking torque coefficient and the accessory power limit value with the task session identifier and the parameter version identifier, and then transmitting the task session identifier, the parameter version identifier and the parameter version identifier to the traction control module and the accessory control module.
6. The method for whole vehicle energy management and endurance optimization of a low-speed four-wheel electric vehicle according to claim 1, wherein S4 comprises: the vehicle controller acquires a traction energy accumulation value and an accessory energy accumulation value according to a sampling period; calculating an energy deviation ratio according to the traction energy budget and the accessory energy budget, obtaining residual energy according to the battery state of charge and the available battery energy, and comparing the residual energy with an energy envelope curve; The vehicle controller generates a subsequent task completion risk index according to a risk mapping relation based on the energy deviation proportion, the deviation degree of residual energy and an envelope curve and a subsequent energy budget, and reduces the traction power upper limit and the accessory power limit by adopting a conservation strategy when the traction control module information and the accessory control module information are detected to be not updated.
7. The method for whole vehicle energy management and endurance optimization of a low-speed four-wheel electric vehicle according to claim 1, wherein S5 comprises: The vehicle controller reads the traction energy deviation ratio, the accessory energy deviation ratio and the maximum task completion risk index of the guarantee unit when the energy-saving regulation period is finished; And searching and obtaining a basic energy-saving adjustment coefficient based on the energy-saving adjustment coefficient mapping table, and correcting according to the change trend of the maximum task completion risk index to obtain the energy-saving adjustment coefficient.
8. The method for managing and optimizing the whole vehicle energy of the low-speed four-wheel electric vehicle according to claim 7, wherein the vehicle controller reduces traction power upper limit, vehicle speed limit and acceleration limit according to traction adjustment weight according to task unit types and energy-saving adjustment coefficients, amplifies regenerative braking torque coefficient according to regenerative adjustment weight and is constrained by battery charging current upper limit, and reduces power limit of comfort related accessories according to accessory compression ratio; The traction power upper limit and comfort related accessory power limit are backed-off to the conservative traction power upper limit and conservative accessory power limit when the risk over high marker is recorded.
9. The method for whole vehicle energy management and endurance optimization of a low-speed four-wheel electric vehicle according to claim 1, wherein S6 comprises: After each task is finished, the vehicle controller updates an energy characteristic table and an energy fluctuation range in a historical observation task window based on task operation records; And generating rule version identifiers and threshold version identifiers after each update, and writing new and old version identifiers and task key indexes into a log area only in an additional writing mode to realize version locking and parameter tracing.

Description

Whole vehicle energy management and endurance optimization method for low-speed four-wheel electric vehicle Technical Field The invention relates to the technical field of energy management of electric vehicles, in particular to a whole vehicle energy management and endurance optimization method of a low-speed four-wheel electric vehicle. Background The existing low-speed four-wheel electric vehicle is widely applied to scenes such as park commute, community riding instead of walk, terminal distribution and the like, and the vehicle is usually started and stopped for many times, bought and unloaded in a fixed or semi-fixed route. In the prior art, the whole vehicle energy management is usually controlled by taking the current state of charge of a single vehicle as a main part, and most strategies such as fixed lower limit threshold value of charge, mileage estimation, simple low-power limit work and nearest charging point searching are adopted, and a small number of schemes are combined with factors such as ambient temperature, average energy consumption and the like to correct the endurance mileage. However, the total energy demand is roughly estimated from the whole vehicle view, the energy distribution between different stop points and task sections is not refined, the importance degree of the tasks of each stop point is not distinguished, the whole vehicle can only conservatively reduce the power or temporarily interrupt the tasks when the energy is intense, and whether the critical stop points can finish the lack of fine and controllable guarantee according to the plan is caused. In some improvements, although the historical operation data is utilized to carry out statistical analysis on the whole vehicle energy consumption, more of the historical operation data stays on the level of 'single task total energy consumption' and 'average energy consumption', the stop point sequence, the loading condition difference and the task completion record in the task information are not combined, the structured modeling is carried out on the task process according to the stop points or the task units, the target energy track which monotonously descends along with the task propulsion is not normally constructed before the task starts, and a systematic planning mechanism for separately restraining the traction energy and the accessory energy is further lacked. Therefore, when the available energy of the battery is close to the critical level for completing the task, the prior art is difficult to identify which stop points belong to the critical level which must be guaranteed and which can be compressed or abandoned, and the completion risk of the subsequent task is difficult to quantify early, the on-site judgment can be carried out only by relying on the experience of a driver, and great uncertainty exists in the cruising performance and the task completion condition. Based on this, under the task scenario of the low-speed four-wheel electric vehicle with stronger repeatability, an energy management method is still needed, which can combine task information and historical task records before the task starts, carry out hierarchical statistics and planning on traction energy and accessory energy demands of different task units, pre-allocate energy budgets of all task units under the constraint of available energy and lower limit of charge of a battery and form a clear target energy evolution track, and combine actual energy deviation and residual energy in the execution process to quantitatively evaluate the completion risk of the subsequent task, so as to solve the problems of insufficient planning and disjointing of task structures and energy, insufficient guarantee capability of key stop points and untimely exposure of energy deficiency risks in the prior art. Disclosure of Invention Aiming at the defects of the prior art, the invention provides a whole vehicle energy management and endurance optimization method of a low-speed four-wheel electric vehicle, which aims to solve the problems in the background art. In order to achieve the purpose, the invention provides the following technical scheme that the whole vehicle energy management and endurance optimization method of the low-speed four-wheel electric vehicle comprises the following steps: S1, acquiring task information and historical data, dividing a guarantee unit, a compressible unit and a sacrificial unit, and counting the traction energy and accessory energy characteristics of each task unit; S2, under the constraint of available energy and a lower limit of charge of a battery, distributing traction energy budget and accessory energy budget for each task unit according to energy characteristics and priorities to form an accumulated energy envelope; S3, generating a control parameter set consisting of a traction power upper limit, a regenerative braking torque coefficient and an accessory power limit value for each task unit based on the energy envelope, an