A vehicle energy management method, apparatus, device, medium and product

Abstract

The application discloses a kind of vehicle energy management method, device, equipment, medium and product, it is related to vehicle energy management technical field.The method comprises: the state data of target vehicle is collected;State data includes speed and pedal position;Determine driving demand power based on speed and pedal position;Based on state data, first coordination parameter, second coordination parameter and battery state of charge reference value, construct target function;In the engine power feasible region and battery power feasible region of target vehicle, the target function is solved, the first engine output power corresponding to the minimum target function value is obtained, and the first engine output power is used as target engine output power;Determine target battery output power based on driving demand power and target engine output power;Based on target engine output power and target battery output power, energy control is carried out to target vehicle.Through the above technical scheme, the efficiency of vehicle energy management can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle energy management, and in particular to a vehicle energy management method, device, equipment, medium and product. BACKGROUND

[0002] Hybrid electric vehicles greatly improve fuel economy by virtue of the efficient cooperation of engines and motors, and have become an important development direction in the automotive field. Among them, the energy management strategy, as the core control technology of hybrid electric vehicles, bears the heavy responsibility of real-time decision-making of power distribution between the engine and the motor, and plays a key role in vehicle performance and energy consumption.

[0003] There are various types of existing energy management strategies, including rule-based control strategies, instantaneous optimization control strategies (such as minimum equivalent fuel consumption strategy), and global optimization control strategies. The main optimization objectives of these strategies are focused on instantaneous fuel economy or fuel consumption of a single trip. However, they all have a major defect: they treat the power battery as an ideal energy unit, ignoring the problem that the state of health of the battery will gradually deteriorate with the charging and discharging cycles in actual use.

[0004] The degradation of the power battery is a complex electrochemical process, which is affected by many factors such as temperature, charging and discharging rate, discharge depth, and cycle number. Frequent high-power charging and discharging operations, as well as operation of the battery at a high or low state of charge, will accelerate the aging process of the battery. Traditional energy management strategies often instruct the battery to perform aggressive charging and discharging operations in pursuit of the best instantaneous fuel economy. For example, during vehicle acceleration, the battery is required to discharge at high power to provide strong power; during braking, the battery is required to charge at high power to recover energy. In the long run, this control strategy undoubtedly sacrifices the battery life at the cost of fuel consumption.

[0005] For the overall value of the vehicle, the cost of the battery pack is extremely high. An energy management strategy that fully considers the state of health of the battery, although it may reduce fuel consumption in the short term, will result in higher maintenance costs and battery replacement costs from the perspective of the vehicle's life cycle cost, and the economic efficiency will be greatly discounted.

[0006] Therefore, there is an urgent need for a new energy management strategy that can optimize the state of health of the battery into the real-time decision-making closed loop to achieve the best balance between fuel economy and battery life. SUMMARY

[0007] The present application provides a vehicle energy management method, device, equipment, medium and product to solve the problem that the existing vehicle energy management method cannot achieve the best balance between fuel economy and battery life.

[0008] According to an aspect of the present application, a vehicle energy management method is provided, comprising:

[0009] collecting state data of a target vehicle; the state data comprises vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed;

[0010] determining driving demand power based on the vehicle speed and the pedal position;

[0011] constructing a target function based on the state data, a first co-state parameter, a second co-state parameter and a battery state of charge reference value;

[0012] solving the target function within an engine power feasible region and a battery power feasible region of the target vehicle to obtain a first engine output power corresponding to a minimum target function value, and taking the first engine output power as a target engine output power;

[0013] determining a target battery output power based on the driving demand power and the target engine output power;

[0014] controlling energy of the target vehicle based on the target engine output power and the target battery output power.

[0015] According to another aspect of the present application, a vehicle energy management device is provided, comprising:

[0016] a vehicle data collection module for collecting state data of a target vehicle; the state data comprises vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed;

[0017] a demand power determination module for determining driving demand power based on the vehicle speed and the pedal position;

[0018] a function construction module for constructing a target function based on the state data, a first co-state parameter, a second co-state parameter and a battery state of charge reference value;

[0019] a function solving module for solving the target function within an engine power feasible region and a battery power feasible region of the target vehicle to obtain a first engine output power corresponding to a minimum target function value, and taking the first engine output power as a target engine output power;

[0020] a target battery output power determination module for determining a target battery output power based on the driving demand power and the target engine output power;

[0021] A vehicle energy control module is configured to perform energy control on a target vehicle based on the target engine output power and the target battery output power.

[0022] According to another aspect of the present application, there is provided an electronic device comprising:

[0023] at least one processor; and a memory connected with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the vehicle energy management method according to any one of the embodiments of the present application.

[0024] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to perform the vehicle energy management method according to any one of the embodiments of the present application when the computer instructions are executed by the processor.

[0025] According to another aspect of the present application, there is provided a computer program product comprising computer program / instructions for enabling a processor to perform the vehicle energy management method according to any one of the embodiments of the present application when the computer program / instructions are executed by the processor.

[0026] The embodiments of the present application collect state data of a target vehicle, wherein the state data comprises vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed; determine driving demand power based on the vehicle speed and the pedal position; construct a target function based on the state data, first co-state parameters, second co-state parameters and battery state of charge reference value; solve the target function within an engine power feasible region and a battery power feasible region of the target vehicle to obtain a first engine output power corresponding to a minimum target function value, and take the first engine output power as a target engine output power; determine a target battery output power based on the driving demand power and the target engine output power; and perform energy control on the target vehicle based on the target engine output power and the target battery output power. Thus, the battery service life is effectively prolonged and the vehicle life cycle operation cost is reduced under the premise of ensuring power, thereby providing an efficient and feasible solution for energy management of a hybrid electric vehicle.

[0027] It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to make the technical solution in the embodiments of the present application clearer, the drawings needed in the embodiments description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0029] Figure 1 is a flow chart of a vehicle energy management method provided by an embodiment of the present application;

[0030] Figure 2 is a flow chart of another vehicle energy management method provided by an embodiment of the present application;

[0031] Figure 3 is a structural schematic diagram of a vehicle energy management device provided by an embodiment of the present application;

[0032] Figure 4 is a structural schematic diagram of an electronic device for implementing the vehicle energy management method of an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to make the technical solution in the embodiments of the present application clearer, the drawings needed in the embodiments description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0034] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily have to include only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0035] In addition, it also needs to be explained that, in the technical solutions of the present application, the collected information is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of related data comply with relevant laws, regulations and standards of relevant countries and regions, necessary security measures are taken, public order and good customs are not violated, and corresponding operation entrances are provided for the user to choose authorization or refusal.

[0036] Figure 1 is a flowchart of a vehicle energy management method provided by an embodiment of the present application. The embodiment can be applicable to the case of energy management of a vehicle, especially to the case of energy management of a hybrid vehicle. The method can be executed by a vehicle energy management device, which can be realized in the form of hardware and / or software, and can be configured in an electronic device with corresponding data processing capability, such as a server. As shown in the figure, the method comprises the following steps. Figure 1

[0037] S110, collecting state data of a target vehicle; the state data comprises vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed.

[0038] The target vehicle is a vehicle that needs to be managed in energy. The state data is the data reflecting the running state of the target vehicle. The vehicle speed is the driving speed of the target vehicle. The pedal includes an accelerator pedal and a brake pedal. The pedal position is the angle of the pedal. The pedal position can reflect the intention of the driver. The current battery state of charge is the remaining capacity of the battery. The battery temperature is the real-time temperature of the battery when working. The temperature that is too high or too low will affect the performance and service life of the battery. The battery temperature is an important parameter limiting the output power of the battery or the power absorbed by the battery. The battery current is the current size when the battery is charging or discharging. When discharging, it is a positive current (power supply for the vehicle), and when charging, it is a negative current (recycling electric energy). The battery voltage is the real-time voltage between the two ends of the battery, which can reflect the health status of the battery and the trend of the remaining capacity. The engine speed is the number of revolutions per minute of the engine crankshaft, and the speed is directly related to the output power of the engine.

[0039] Specifically, the state data of the target vehicle is collected, which includes vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed. Thus, based on the collected data, the running condition of the target vehicle is understood, such as vehicle speed (reflecting the speed of vehicle driving), pedal position (i.e. the depth of accelerator or brake pedal, reflecting the intention of the driver, and the intention of the driver includes acceleration or deceleration), and current battery state of charge (reflecting the current remaining capacity of the battery).

[0040] S120, determining the driving demand power based on the vehicle speed and the pedal position. ​

[0041] wherein the driving demand power is a power that the target vehicle currently needs to output.

[0042] Specifically, the driving demand power of the target vehicle is calculated according to the speed of the target vehicle and the pedal position. For example, if the driver steps on the accelerator very deeply (the accelerator pedal position angle is large), and the speed of the target vehicle is not high, it indicates that the driver wants to accelerate, and the target vehicle needs a large output power at this moment. If the speed of the target vehicle is high and the driver steps on the accelerator lightly or not at all, it indicates that the target vehicle only needs a small power to maintain driving at this moment. The driving demand power tells the power system (such as the engine and the motor) of the target vehicle how much force to output, so as to make the driving more smooth. Thus, the driving demand power is determined through the speed and the pedal position, and the power output of the target vehicle is matched with the driving intention of the driver.

[0043] S130, constructing a target function based on the state data, the first co-state parameter, the second co-state parameter and the battery state of charge reference value.

[0044] The first co-state parameter is a key equivalent factor for balancing the instantaneous fuel economy and the long-term battery life. The function of the first co-state parameter is to convert the long-term cost of battery health degradation into instantaneous fuel cost, so as to realize the equivalent measurement of the two in the optimization process. The second co-state parameter is a co-state parameter related to the battery state of charge. The second co-state parameter is used to reflect the sensitivity of the control system of the target vehicle to the deviation of the battery state of charge from the battery state of charge reference value. The function of the second co-state parameter is to act as a stabilizer of the battery state of charge, so as to ensure that the battery state of charge is maintained in a reasonable range centered on the battery state of charge reference value in the process of energy management of the target vehicle. The battery state of charge reference value is a standard value of the battery state of charge preset in advance. The battery state of charge reference value is usually 0.5-0.6. The battery state of charge reference value is used to ensure sufficient charging and discharging buffer space. The target function is a function for solving the problem of vehicle energy management.

[0045] Specifically, the state data of the target vehicle, the first co-state parameter, the second co-state parameter and the battery state of charge reference value are integrated to establish a mathematical formula (i.e., the target function) for optimizing the energy management of the target vehicle. That is, the key factors affecting the decision of vehicle energy management are put into a mathematical model, and the optimal solution can be found by subsequent calculation.

[0046] S140, solving the target function in the engine power feasible region and the battery power feasible region of the target vehicle to obtain the first engine output power corresponding to the minimum target function value, and taking the first engine output power as the target engine output power.

[0047] The engine power feasible region is a power range output by the engine, and the power range includes an upper limit and a lower limit. The upper limit is a maximum output power designed for the engine, and the lower limit is a minimum output power for maintaining the engine operation without being turned off. The battery power feasible region is a power range output by the battery, and the power range includes an output power and an absorption power. The output power (positive power) is a maximum output power when the battery supplies power to the vehicle, and the absorption power (negative power) is a power upper limit when the battery recovers power during deceleration of the vehicle. The first engine output power is an engine output power corresponding to a minimum value of the target function. The target engine output power is an engine output power to be finally executed by the target vehicle.

[0048] Specifically, the target function is solved within the engine power feasible region and the battery power feasible region of the target vehicle, and the first engine output power corresponding to a minimum value of the target function is calculated. The first engine output power is taken as the target engine output power. Thus, the target engine output power meets the driving demand and meets the optimization target. For example, the engine power feasible region can be expressed as: wherein, Pmin is the minimum output power of the engine, Pmax is the maximum output power of the engine, P(t) is the engine output power at time t. The battery power feasible region can be expressed as: wherein, Pmin is the minimum output power of the battery, Pmax is the maximum output power of the battery, P(t) is the battery output power.

[0049] S150, based on the driving demand power and the target engine output power, determining a target battery output power.

[0050] The target battery output power is an output power to be finally executed by the target vehicle.

[0051] Specifically, the driving demand power is the total power required by the target vehicle at the moment, which is satisfied by the engine and the battery together. The difference between the driving demand power and the target engine output power can be taken as the target battery output power. For example, if the driving demand power is greater than the target engine output power, the battery needs to output the difference to help the vehicle make up the power (for example, when accelerating, the engine power is not enough, and the battery assists power supply); if the driving demand power is less than the target engine output power: the battery needs to absorb the excess power (at this time, it is negative power, that is, to recover electric energy), to avoid waste of power (for example, when driving at a constant speed, the engine output is slightly higher than the demand, and the excess power charges the battery); if they are equal: the battery does not output or absorb, and only the engine provides power. Thus, the engine and the battery work together accurately to meet the driving demand while meeting the optimization target, protecting the power system safety, making the power distribution more reasonable, avoiding the situation of power being too much or too little, and improving the driving experience.

[0052] S160, based on the target engine output power and the target battery output power, performing energy control on the target vehicle.

[0053] Specifically, the engine of the target vehicle is controlled to work according to the target engine output power, and the battery of the target vehicle is controlled to work according to the target battery output power, so as to realize reasonable distribution and control of energy of the target vehicle.

[0054] Optionally, based on the state data, the first coordination state parameter, the second coordination state parameter and the battery state of charge reference value, a target function is constructed, including: determining an instantaneous fuel consumption rate based on the second engine output power and the engine speed; determining a battery health state decay rate based on the current battery state of charge, the battery temperature, the battery current and the battery voltage; and constructing the target function based on the instantaneous fuel consumption rate, the first coordination state parameter, the battery health state decay rate, the second coordination state parameter, the current battery state of charge and the battery state of charge reference value.

[0055] The second engine output power is the engine output power to be solved. The instantaneous fuel consumption rate refers to the amount of fuel consumed by the engine per unit power output at a certain time. The battery health state decay rate is used to reflect the decay speed of the battery health state.

[0056] Specifically, the instantaneous fuel consumption rate is determined based on the second engine output power and the engine speed through the engine universal characteristic map stored in the system. The engine universal characteristic map is a two-dimensional curve graph that visually displays the relationship between the engine speed, the engine output power and the instantaneous fuel consumption rate. The engine universal characteristic map can be expressed as: wherein, is the instantaneous fuel consumption rate, is the engine output power, is the engine speed. The battery state of health degradation rate is determined based on the current battery state of charge, battery temperature, battery current, and battery voltage through the battery state of health degradation model. The battery state of health degradation model can be expressed as: wherein, is the battery temperature, is the battery current, SOC is the battery state of charge, and t is the time, is the battery state of health degradation rate, is used to reflect the damage degree of each Ah of electricity to the battery state of health under the current working condition (battery temperature, battery current, SOC), SOH is the battery state of health, and Ah is the unit of battery capacity, is the real-time battery current absolute value, represents the instantaneous charging and discharging rate. For example, if the model is , then the battery SOH decreases by 0.02% for each 1 Ah of electricity throughput. The unit Ah throughput refers to the standardized damage to the battery health when the battery charges or discharges 1 Ah of electricity. The objective function is constructed based on the instantaneous fuel consumption rate, the first co-state parameter, the battery state of health degradation rate, the second co-state parameter, the current battery state of charge, and the battery state of charge reference value. The objective function can be expressed as:

[0057] ;

[0058] wherein, is the engine output power at time t, is the fuel consumption rate when the engine runs at power , is the first co-state parameter, is the second co-state parameter, is the battery state of health degradation rate, is the battery state of charge at time t, is the battery state of charge reference value, is the objective function value at time t.

[0059] Thus, by including in the objective function H(t), the fuel economy of the engine can be considered in the optimization process to find the engine power output strategy that minimizes fuel consumption. By introducing the battery state of health degradation term into the objective function, the battery life cost is directly included in the instantaneous optimization decision, and by introducing The control requirement of the battery SOC is incorporated into the optimization process, so as to prompt the algorithm to adjust the power distribution of the engine and the battery in the optimization process, so that the battery SOC returns to the vicinity of the reference value as soon as possible. Through this feedback mechanism, the power distribution of the engine and the battery is automatically coordinated, the sustainability of the battery energy source is ensured while the instantaneous optimum is pursued.

[0060] Optionally, based on the target engine output power and the target engine output power, the energy of the target vehicle is controlled, including: based on the engine speed and the target engine output power, the target engine torque is determined; based on the target engine torque, the engine of the target vehicle is controlled; based on the target battery output power, the motor of the target vehicle is controlled.

[0061] The target engine torque is the actual force size that the engine needs to output, and is a direct instruction to control the engine power.

[0062] Specifically, based on the engine speed and the target engine output power, the target engine torque is calculated; based on the target engine torque, the engine of the target vehicle is controlled, that is, the target engine torque is converted into a specific control instruction (such as adjusting the fuel injection amount and the throttle opening), so that the actual output torque of the engine is just equal to the target value, thereby realizing the control of the engine of the target vehicle; based on the target battery output power, the current or voltage of the motor is adjusted, so that the actual output power of the motor is equal to the target value, thereby realizing the control of the motor of the target vehicle. For example, if the target battery output power is 30kW, the motor is controlled to release 30kW of electric energy for auxiliary driving; if the target battery output power is -20kW (negative power), the motor is controlled to recover 20kW of electric energy to charge the battery. Therefore, the power output of the engine and the motor not only meets the driving demand, but also follows the optimal energy distribution scheme, so that the vehicle power system works accurately according to the plan.

[0063] The embodiment of the application acquires state data of a target vehicle; the state data includes vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed; determines driving demand power based on the vehicle speed and the pedal position; constructs a target function based on the state data, a first co-state parameter, a second co-state parameter and a battery state of charge reference value; solves the target function within an engine power feasible region and a battery power feasible region of the target vehicle to obtain a first engine output power corresponding to a minimum target function value, and takes the first engine output power as a target engine output power; determines a target battery output power based on the driving demand power and the target engine output power; and controls energy of the target vehicle based on the target engine output power and the target battery output power. Thus, the battery service life is effectively prolonged and the vehicle life cycle operation cost is reduced under the premise of ensuring power, thereby providing an efficient and feasible solution for energy management of a hybrid electric vehicle.

[0064] Figure 2 is a flowchart of another vehicle energy management method provided by the embodiment of the application, and the embodiment optimizes the updating methods of the first co-state parameter and the second co-state parameter based on the above-mentioned embodiment, and provides an optional implementation scheme. As shown in Figure 2 , the method comprises:

[0065] S210, acquiring state data of a target vehicle; the state data includes vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed.

[0066] S220, determining driving demand power based on the vehicle speed and the pedal position.

[0067] S230, constructing a target function based on the state data, a first co-state parameter, a second co-state parameter and a battery state of charge reference value.

[0068] S240, solving the target function within an engine power feasible region and a battery power feasible region of the target vehicle to obtain a first engine output power corresponding to a minimum target function value, and taking the first engine output power as a target engine output power.

[0069] S250, determining a target battery output power based on the driving demand power and the target engine output power.

[0070] S260, controlling energy of the target vehicle based on the target engine output power and the target battery output power.

[0071] Optionally, the updating manner of the first cooperative state parameter comprises: determining a battery thermal stress coefficient, a battery electrical stress coefficient and a trip characteristic coefficient; converting the battery thermal stress coefficient, the battery electrical stress coefficient and the trip characteristic coefficient through a membership function to obtain fuzzy language variables; processing the fuzzy language variables based on a fuzzy rule base to obtain a first change; and updating the first cooperative state parameter based on a gain coefficient and the first change.

[0072] The battery thermal stress coefficient is used to reflect the loss pressure caused by the battery temperature. The battery electrical stress coefficient is used to reflect the loss pressure caused by the battery charging and discharging intensity. The trip characteristic coefficient is a predictive parameter reflecting the intensity of future driving. The membership function is a mathematical tool that can convert specific numerical values into fuzzy language variables. The gain coefficient is a preset parameter used to control the adaptive speed and prevent the system from oscillating due to the rapid change of the first cooperative state parameter. The value of the gain coefficient can be optimized through experiments or simulations, and the specific value can be adjusted according to the response speed and stability requirements of the system.

[0073] Specifically, the battery thermal stress coefficient, the battery electrical stress coefficient and the trip characteristic coefficient are determined; the battery thermal stress coefficient, the battery electrical stress coefficient and the trip characteristic coefficient are converted through the membership function to obtain fuzzy language variables, which include low, medium and high, for example, if the battery thermal stress coefficient is 0.7 and the battery electrical stress coefficient is 0.3, they are converted through the membership function to obtain a battery thermal stress coefficient of high and a battery electrical stress coefficient of low; the fuzzy language variables are subjected to fuzzy reasoning based on the rules in the fuzzy rule base to obtain output variables, and the output variables are defuzzified using the gravity method to obtain a first change, which is an accurate output value; and the gain coefficient and the first change are used to update the first cooperative state parameter.

[0074] Optionally, the updating formula of the first cooperative state parameter is: new first cooperative state parameter = old first cooperative state parameter + gain coefficient x first change. When the system is powered on for the first time or has no historical data, the first cooperative state parameter can be set to a conservative median value, for example, the first cooperative state parameter is 1.0, which means that the system defaults to considering the fuel cost and the battery life cost as equally important. After a small number of driving cycles, the adaptive strategy will continuously adjust the value of the first cooperative state parameter based on real-time battery status, vehicle driving data and other information, and gradually approach the optimal solution through a feedback mechanism to adapt to the current driving style and environmental conditions. For example, if the product of the gain coefficient and the first change is 0.1, the first cooperative state parameter is increased by 0.1 to obtain a new first cooperative state parameter, thereby updating the first cooperative state parameter.

[0075] Thus, by collecting actual vehicle condition factors, avoiding absolutization through fuzzy processing, and quantitatively adjusting parameters, the first coordination parameter always fits the battery state and driving scene, and when the subsequent optimization target function is optimized, a more accurate power distribution scheme can be given.

[0076] Optionally, the content of the fuzzy rule base can be as follows, wherein the battery thermal stress coefficient is (T), the battery electric stress coefficient is (C), the trip characteristic coefficient is (S), represents an output variable,

[0077]

[0078] Optionally, determining the battery thermal stress coefficient, the battery electric stress coefficient, and the trip characteristic coefficient comprises: obtaining historical battery data and historical vehicle speed data; the historical battery data comprises a temperature average value of historical battery temperature and a root mean square value of historical battery current absolute value; the historical vehicle speed data comprises a historical average vehicle speed; determining the battery thermal stress coefficient based on the temperature average value, a first temperature threshold, and a second temperature threshold; determining the battery electric stress coefficient based on the root mean square value, a battery rated capacity, and a first current threshold; and determining the trip characteristic coefficient based on the historical average vehicle speed, a first speed threshold, and a second speed threshold.

[0079] Wherein, the historical battery data is the battery data of the last period of the current period. The historical vehicle speed data is the vehicle speed data of the last period of the current period. The historical battery temperature is the battery temperature of the last period of the current period. The historical battery current is the battery current of the last period of the current period. The historical average vehicle speed is the average value of the vehicle speed of the last period of the current period.

[0080] Optionally, the battery thermal stress coefficient can be represented as:

[0081] ;

[0082] Wherein, is the battery thermal stress coefficient, is the temperature average value of the historical battery temperature, the first temperature threshold is 25 , and the second temperature threshold is 50 . The optimal working temperature range of the battery is usually . The battery temperature data is the temperature sensor data provided by the battery management system. The range of the battery thermal stress coefficient is [0, 1]. 0 represents low temperature (no thermal stress), and 1 represents high temperature (high thermal stress).

[0083] Optionally, the battery electric stress coefficient can be represented as:

[0084] ;

[0085] wherein, is a battery electric stress coefficient, is a battery rated capacity, is a root mean square value of historical battery current absolute value, and the first current threshold is 1. The unit of the battery rated capacity is Ah. The battery current data is the current sensor data provided by the battery management system. The range of the battery electric stress coefficient is [0, 1]. 0 represents no current (no electric stress), and 1 represents continuous work at 1C or higher (high electric stress).

[0086] Optionally, the trip feature coefficient can be expressed as:

[0087] ;

[0088] wherein, is a trip feature coefficient, is a historical average vehicle speed, the first speed threshold is 20, and the second speed threshold is 100. The speed signal of the vehicle can be obtained through the CAN bus, and the average vehicle speed of the last period of the current period is calculated. The unit of the historical average vehicle speed is km / h. The range of the trip feature coefficient is [0, 1]. Close to 0 represents severe congestion (frequent start-stop, high requirement for the battery), and close to 1 represents high-speed cruising (smooth working condition, friendly to the battery).

[0089] Optionally, the updating method of the second cooperative state parameter is as follows: according to the current battery state of charge of the target vehicle and the battery state of charge reference value, a current battery state of charge difference is determined; according to the historical battery state of charge of the target vehicle at the historical time and the battery state of charge reference value, a historical battery state of charge difference is determined; and based on a proportional gain, an integral gain, the current battery state of charge difference and the historical battery state of charge difference, the second cooperative state parameter is updated.

[0090] Specifically, the difference between the current battery state of charge of the target vehicle and the battery state of charge reference value is determined as the current battery state of charge difference; the difference between the historical battery state of charge of the target vehicle at the historical time and the battery state of charge reference value is determined as the historical battery state of charge difference; and based on the proportional gain, the integral gain, the current battery state of charge difference and the historical battery state of charge difference, the second cooperative state parameter is updated. Thus, through the current and historical electric quantity deviations, combined with the proportional and integral adjustment method, the second cooperative state parameter dynamically adapts to the battery electric quantity state, and in subsequent optimization of the target function, the driving demand can be better met and the battery reasonable electric quantity can be maintained.

[0091] Optionally, the updating formula of the second cooperative state parameter can be expressed as:

[0092] ;

[0093] in, For the second costate parameter, For proportional gain, For integral gain, This represents the current state of battery charge. This is a reference value for the battery's state of charge. Due to poor historical state of charge of the battery, The current battery state of charge difference is given by t, where t is the current system time. It is the integration variable in the integral, used to iterate through all time points from a certain point in the past to the current time t. It is a local variable of the integration, meaningful only during the integration process and not representing a specific time. t is the upper limit of the integration, representing the endpoint of the integration process.

[0094] This invention continuously adjusts the value of the first costate parameter based on real-time battery status, vehicle driving data, and other information, gradually approaching the optimal solution through a feedback mechanism to adapt to current driving style and environmental conditions. This invention also dynamically adapts the second costate parameter to the battery status by adjusting the current and historical battery level deviation using proportional and integral methods. This allows for better fulfillment of driving needs and maintenance of a reasonable battery level during subsequent optimization of the objective function.

[0095] Figure 3 This is a schematic diagram of a vehicle energy management device provided in an embodiment of the present invention. This embodiment is applicable to situations involving vehicle energy management, particularly hybrid electric vehicles. The device can be implemented in hardware and / or software and can be configured in an electronic device with corresponding data processing capabilities, such as a server. Figure 3 As shown, the device includes:

[0096] The vehicle data acquisition module 310 is used to collect the status data of the target vehicle; the status data includes vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed;

[0097] The power demand determination module 320 is used to determine the driving power demand based on vehicle speed and pedal position;

[0098] The function construction module 330 is used to construct an objective function based on state data, a first costate parameter, a second costate parameter, and a battery state of charge reference value.

[0099] The function solving module 340 is configured to solve the target function in the engine power feasible region and the battery power feasible region of the target vehicle, to obtain a first engine output power corresponding to a minimum target function value, and to take the first engine output power as the target engine output power.

[0100] The target battery output power determination module 350 is configured to determine the target battery output power based on the driving demand power and the target engine output power.

[0101] The vehicle energy control module 360 is configured to perform energy control on the target vehicle based on the target engine output power and the target battery output power.

[0102] The embodiment of the present application collects the state data of the target vehicle, wherein the state data includes the vehicle speed, the pedal position, the current battery state of charge, the battery temperature, the battery current, the battery voltage and the engine speed; determines the driving demand power based on the vehicle speed and the pedal position; constructs the target function based on the state data, the first coordination parameter, the second coordination parameter and the battery state of charge reference value; solves the target function in the engine power feasible region and the battery power feasible region of the target vehicle, to obtain a first engine output power corresponding to a minimum target function value, and takes the first engine output power as the target engine output power; determines the target battery output power based on the driving demand power and the target engine output power; and performs energy control on the target vehicle based on the target engine output power and the target battery output power. Thus, the battery service life is effectively prolonged and the vehicle life cycle operation cost is reduced under the premise of ensuring the power, thereby providing an efficient and feasible solution for the energy management of the hybrid electric vehicle.

[0103] Optionally, the function constructing module 330 comprises:

[0104] The instantaneous fuel consumption rate determination unit is configured to determine the instantaneous fuel consumption rate based on the second engine output power and the engine speed.

[0105] The battery health state attenuation rate determination unit is configured to determine the battery health state attenuation rate based on the current battery state of charge, the battery temperature, the battery current and the battery voltage.

[0106] The target function constructing unit is configured to construct the target function based on the instantaneous fuel consumption rate, the first coordination parameter, the battery health state attenuation rate, the second coordination parameter, the current battery state of charge and the battery state of charge reference value.

[0107] Optionally, the device further comprises a first coordination parameter updating module.

[0108] Optionally, the first coordination parameter updating module comprises:

[0109] a coefficient determination unit configured to determine a battery thermal stress coefficient, a battery electric stress coefficient, and a trip feature coefficient;

[0110] a fuzzy variable determination unit configured to convert the battery thermal stress coefficient, the battery electric stress coefficient, and the trip feature coefficient into fuzzy language variables by using a membership function;

[0111] a change amount determination unit configured to process the fuzzy language variables based on a fuzzy rule base to obtain a first change amount;

[0112] a first parameter updating unit configured to update the first co-state parameter based on a gain coefficient and the first change amount.

[0113] Optionally, the coefficient determination unit is specifically configured to: obtain historical battery data and historical vehicle speed data; the historical battery data includes a temperature average value of historical battery temperature and a root mean square value of historical battery current absolute value; the historical vehicle speed data includes a historical average vehicle speed; determine the battery thermal stress coefficient based on the temperature average value, a first temperature threshold, and a second temperature threshold; determine the battery electric stress coefficient based on the root mean square value, a battery rated capacity, and a first current threshold; and determine the trip feature coefficient based on the historical average vehicle speed, a first speed threshold, and a second speed threshold.

[0114] Optionally, the device further includes a second co-state parameter updating module.

[0115] Optionally, the second co-state parameter updating module includes:

[0116] a current battery state of charge difference determination unit configured to determine a current battery state of charge difference according to a current battery state of charge of the target vehicle and a battery state of charge reference value;

[0117] a historical battery state of charge difference determination unit configured to determine a historical battery state of charge difference according to a historical battery state of charge of the target vehicle at a historical time and the battery state of charge reference value;

[0118] a second parameter updating unit configured to update the second co-state parameter based on a proportional gain, an integral gain, the current battery state of charge difference, and the historical battery state of charge difference.

[0119] Optionally, the vehicle energy control module 360 includes:

[0120] a target engine torque determination unit configured to determine a target engine torque based on an engine speed and a target engine output power;

[0121] an engine control unit configured to control an engine of the target vehicle based on the target engine torque;

[0122] The motor control unit is configured to control a motor of the target vehicle based on a target battery output power.

[0123] The vehicle energy management device provided by the embodiments of the present application can execute the vehicle energy management method provided by any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0124] According to the embodiments of the present application, the present application further provides an electronic device, a readable storage medium and a computer program product.

[0125] Figure 4 A structural schematic diagram of an electronic device 10 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit implementations of the present application described and / or claimed in this document.

[0126] As shown in Figure 4 The electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0127] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunications networks.

[0128] The processor 11 can be various general and / or special purpose processing components having processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the vehicle energy management method.

[0129] In some embodiments, the vehicle energy management method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded onto the RAM 13 and executed by the processor 11, one or more steps of the vehicle energy management method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the vehicle energy management method by any other suitable means, such as by means of firmware.

[0130] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0131] Computer programs used to implement the methods of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0132] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0133] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0134] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0135] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business expansion in traditional physical host and virtual private service.

[0136] It should be understood that the various forms of flow shown above can be reordered, added to, or have steps deleted. For example, the steps described in the present application can be performed in parallel, in series, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, and this is not limited herein.

[0137] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A vehicle energy management method, characterized by, The method comprises: collecting state data of the target vehicle; the state data comprises vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage and engine speed; determining driving demand power based on the vehicle speed and the pedal position; constructing a target function based on the state data, a first co-state parameter, a second co-state parameter and a battery state of charge reference value; solving the target function within the engine power feasible region and the battery power feasible region of the target vehicle to obtain a first engine output power corresponding to the minimum target function value, and taking the first engine output power as a target engine output power; determining a target battery output power based on the driving demand power and the target engine output power; controlling energy of the target vehicle based on the target engine output power and the target battery output power; wherein the constructing of the target function based on the state data, the first co-state parameter, the second co-state parameter and the battery state of charge reference value comprises: determining an instantaneous fuel consumption rate based on the second engine output power and the engine speed; determining a battery health state attenuation rate based on the current battery state of charge, the battery temperature, the battery current and the battery voltage; constructing the target function based on the instantaneous fuel consumption rate, the first co-state parameter, the battery health state attenuation rate, the second co-state parameter, the current battery state of charge and the battery state of charge reference value; wherein the updating mode of the first co-state parameter comprises: obtaining historical battery data and historical vehicle speed data; the historical battery data comprises a temperature average value of historical battery temperature and a root mean square value of historical battery current absolute value; the historical vehicle speed data comprises a historical average vehicle speed; determining a battery thermal stress coefficient based on the temperature average value, a first temperature threshold value and a second temperature threshold value; determining a battery electric stress coefficient based on the root mean square value, a battery rated capacity and a first current threshold value; determining a trip characteristic coefficient based on the historical average vehicle speed, a first speed threshold value and a second speed threshold value; transforming the battery thermal stress coefficient, the battery electric stress coefficient and the trip characteristic coefficient through a membership function to obtain fuzzy language variables; processing the fuzzy language variables based on a fuzzy rule base to obtain a first change value; updating the first co-state parameter based on a gain coefficient and the first change value.

2. The method of claim 1, wherein, The updating mode of the second co-state parameter is as follows: determining a current battery state of charge difference according to the current battery state of charge of the target vehicle and the battery state of charge reference value; determining a historical battery state of charge difference according to a historical battery state of charge of the target vehicle at a historical time and the battery state of charge reference value; updating the second co-state parameter based on a proportional gain, an integral gain, the current battery state of charge difference and the historical battery state of charge difference.

3. The method of claim 1, wherein, The energy control of the target vehicle based on the target engine output power and the target engine output power comprises: determining a target engine torque based on the engine speed and the target engine output power; control an engine of the target vehicle based on the target engine torque; control a motor of the target vehicle based on the target battery output power.

4. A vehicle energy management apparatus, characterized by, The device comprises: a vehicle data collection module configured to collect state data of a target vehicle; the state data comprises vehicle speed, pedal position, current battery state of charge, battery temperature, battery current, battery voltage, and engine speed; a demand power determination module configured to determine driving demand power based on the vehicle speed and the pedal position; a function construction module configured to construct a target function based on the state data, a first co-state parameter, a second co-state parameter, and a battery state of charge reference value; a function solving module configured to solve the target function within an engine power feasible region and a battery power feasible region of the target vehicle to obtain a first engine output power corresponding to a minimum target function value, and take the first engine output power as a target engine output power; a target battery output power determination module configured to determine a target battery output power based on the driving demand power and the target engine output power; a vehicle energy control module configured to control energy of the target vehicle based on the target engine output power and the target battery output power; The function construction module comprises: an instantaneous fuel consumption rate determination unit configured to determine an instantaneous fuel consumption rate based on a second engine output power and the engine speed; a battery health state attenuation rate determination unit configured to determine a battery health state attenuation rate based on the current battery state of charge, the battery temperature, the battery current, and the battery voltage; a target function construction unit configured to construct a target function based on the instantaneous fuel consumption rate, a first co-state parameter, the battery health state attenuation rate, a second co-state parameter, the current battery state of charge, and a battery state of charge reference value. The device further comprises a first co-state parameter updating module configured to: obtain historical battery data and historical vehicle speed data; the historical battery data comprises a temperature average value of historical battery temperature and a root mean square value of historical battery current absolute value; the historical vehicle speed data comprises a historical average vehicle speed; determine a battery thermal stress coefficient based on the temperature average value, a first temperature threshold, and a second temperature threshold; determine a battery electric stress coefficient based on the root mean square value, a battery rated capacity, and a first current threshold; determine a trip characteristic coefficient based on the historical average vehicle speed, a first speed threshold, and a second speed threshold; transform the battery thermal stress coefficient, the battery electric stress coefficient, and the trip characteristic coefficient through a membership function to obtain a fuzzy language variable; process the fuzzy language variable based on a fuzzy rule base to obtain a first change value; and update the first co-state parameter based on a gain coefficient and the first change value.

5. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected in communication with the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the vehicle energy management method of any one of claims 1-3.

6. A computer readable storage medium characterized by, The computer readable storage medium stores computer instructions for causing a processor to implement the vehicle energy management method of any one of claims 1-3 when executed.

7. A computer program product comprising a computer program which, when executed by a processor, implements the vehicle energy management method of any one of claims 1-3.

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