Vehicle energy management method, device, equipment, medium and product

Abstract

The invention discloses a vehicle energy management method, device and equipment, a medium and a product, and relates to the technical field of vehicles. The method comprises the steps of determining a working condition and a load state of a target vehicle based on obtained target state data of the target vehicle; determining a target battery charge state of the target vehicle based on the working condition, the load state and the constraint condition; based on the target state data, fuel consumption cost, battery life cost, power performance loss and driving comfort loss are determined, and then a target function is constructed; in the power feasible region, solving the target function to obtain the output power of the target range extender; determining target battery output power based on the driving demand power and the target range extender output power; and performing energy control on the target vehicle based on the target battery charge state, the target range extender output power and the target battery output power. According to the technical scheme, the vehicle energy management efficiency can be improved.

Description

TECHNICAL FIELD

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

[0002] With the increasingly severe global environmental problems and the gradual depletion of oil resources, new energy vehicles have become an inevitable trend in the development of the automotive industry. As an important type of new energy vehicles, range extended electric vehicles (REEVs) extend the range of pure electric vehicles through a range extender, solving the range anxiety problem of pure electric vehicles and having broad application prospects in the commercial vehicle field.

[0003] However, the energy management of range extended commercial vehicles faces unique challenges. Commercial vehicles have large load capacity, complex working conditions, and long operating time, which puts higher requirements on energy management strategies. How to optimize energy utilization efficiency and extend the range of travel while ensuring power performance is a key issue in the development of range extended commercial vehicles. SUMMARY

[0004] The present application provides a vehicle energy management method, device, equipment, medium and product to solve the problem of low efficiency of vehicle energy management, to maximize energy utilization efficiency, extend the range of travel, and balance battery life and real-time control requirements while ensuring power performance.

[0005] According to an aspect of the present application, a vehicle energy management method is provided, comprising:

[0006] obtaining target state data of a target vehicle;

[0007] determining the working condition and load state of the target vehicle based on the target state data;

[0008] determining the target battery state of charge of the target vehicle based on the working condition, the load state and the constraint condition;

[0009] determining the fuel consumption cost, the battery life cost, the power performance loss and the driving comfort loss based on the target state data;

[0010] constructing a target function based on the fuel consumption cost, the battery life cost, the power performance loss, the driving comfort loss and the weight coefficient;

[0011] solving the target function within the power feasible region to obtain the target range extender output power;

[0012] determining the target battery output power based on the driving demand power and the target range extender output power;

[0013] perform energy control on the target vehicle based on the target battery state of charge, the target range extender output power and the target battery output power.

[0014] According to another aspect of the present application, there is provided a vehicle energy management device, comprising:

[0015] a data acquisition module configured to acquire target state data of a target vehicle;

[0016] a working condition and load state determination module configured to determine a working condition and a load state of the target vehicle based on the target state data;

[0017] a target battery state of charge determination module configured to determine a target battery state of charge of the target vehicle based on the working condition, the load state and a constraint condition;

[0018] a cost loss determination module configured to determine a fuel consumption cost, a battery life cost, a power performance loss and a driving comfort loss based on the target state data;

[0019] a function construction module configured to construct a target function based on the fuel consumption cost, the battery life cost, the power performance loss, the driving comfort loss and a weight coefficient;

[0020] a target range extender output power determination module configured to solve the target function within a power feasible region to obtain a target range extender output power;

[0021] a target battery output power determination module configured to determine a target battery output power based on a driving demand power and the target range extender output power;

[0022] a vehicle control module configured to perform energy control on the target vehicle based on the target battery state of charge, the target range extender output power and the target battery output power.

[0023] According to another aspect of the present application, there is provided an electronic device, comprising:

[0024] at least one processor; and a memory connected with the at least one processor in communication; 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.

[0025] 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 executed by the processor.

[0026] According to another aspect of the present application, there is provided a computer program product comprising computer programs / instructions which, when executed by a processor, implement the vehicle energy management method as described in any embodiment of the present application.

[0027] The embodiments of the present application determine a reasonable target battery state of charge according to the working condition and the load, and subsequent energy control keeps the battery in a safe interval, avoiding the state of deep discharge, high temperature and high power, etc. which damages the battery; the target function integrates the fuel consumption cost, the battery life cost, the power performance loss and the driving comfort loss, and can also be flexibly adjusted through the weight coefficient, i.e. by considering the economy, power performance, battery life and driving comfort, the comprehensive optimization is realized through the weight self-adaption, and then the target vehicle is controlled in energy through the determined target battery state of charge, the target range extender output power and the target battery output power, which realizes the maximization of energy utilization efficiency, prolongs the cruising range, and takes into account the battery life and real-time control requirements under the premise of guaranteeing the power performance.

[0028] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor 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

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0030] Figure 1 is a flow chart of a vehicle energy management method provided by the embodiments of the present application;

[0031] Figure 2 is a flow chart of a vehicle energy management method provided by the embodiments of the present application;

[0032] Figure 3 is a structural schematic diagram of a vehicle energy management device provided by the embodiments of the present application;

[0033] Figure 4 is a structural schematic diagram of an electronic device for implementing the vehicle energy management method of the embodiments of the present application. DETAILED DESCRIPTION

[0034] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application in order to make the technical personnel in the technical field better understand the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the ordinary technical personnel in the technical field without creative labor should belong to the protection scope of the present application.

[0035] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described 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 have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0036] In addition, it should also be noted that in the technical solutions of the present application, the collected information is information and data authorized by the user or 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, do not violate public order and good customs, and provide corresponding operation portal for user to choose authorization or refusal.

[0037] 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 applicable to the case of energy management and optimization of a range-extended electric commercial 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: Figure 1

[0038] S110, obtaining target state data of a target vehicle.

[0039] The target vehicle is a vehicle to be managed in energy. The target state data is the state data in the running process of the vehicle.

[0040] ​Specifically, by collecting state data in the running process of the target vehicle through a vehicle-mounted sensor, a control module, etc., the collected state data is preprocessed to obtain target state data.

[0041] S120, based on the target state data, determining the working condition and load state of the target vehicle.

[0042] Among them, the working condition is the scene type of vehicle driving. The load state is the load level currently carried by the vehicle.

[0043] Specifically, by matching the vehicle running characteristics and load association rules through the key parameters (vehicle speed, acceleration, etc.) in the target state data, the working condition and load state of the target vehicle are determined.

[0044] S130, based on the working condition, load state and constraint condition, determining the target battery state of charge of the target vehicle.

[0045] Among them, the target battery state of charge is the final determined battery state of charge.

[0046] Specifically, the target battery state of charge is calculated in real time in combination with the working condition and load state, and the target battery state of charge meets the constraint condition. For example, the constraint condition can include that the target battery state of charge is limited within the range of 30%-70%, and the change rate of the target battery state of charge is not more than 2%. Thus, while meeting the vehicle driving demand, the battery is maximized to be protected, the energy utilization is optimized, and the system stability and use safety are guaranteed.

[0047] S140, based on the target state data, determining the fuel consumption cost, battery life cost, power performance loss and driving comfort loss.

[0048] Among them, the fuel consumption cost refers to the cost generated by burning fuel when the vehicle is running. The battery life cost is the economic cost after conversion due to the attenuation of the battery caused by use (such as charging and discharging, battery state of charge fluctuation, etc.). The power performance loss refers to the performance gap that the actual power (such as acceleration, climbing, vehicle speed) of the vehicle is worse than the ideal state. The driving comfort loss is the sum of the subjective feeling and objective experience decline caused by the fluctuation of the vehicle running state.

[0049] Specifically, according to the target state data (such as vehicle speed, acceleration, battery state of charge, etc.) of the target vehicle, it is calculated how many kilometers the vehicle runs, how much oil it consumes, how much the battery SOC (State of Charge) changes, whether the vehicle is currently in an acceleration or climbing working condition, whether there is heavy load, etc., so as to determine the fuel consumption cost, battery life cost, power performance loss and driving comfort loss. For example, if the vehicle runs 100 kilometers and consumes 8 liters of oil, and the oil price is 8 yuan per liter, then the fuel consumption cost is 64 yuan; if the battery replacement cost is 100,000 yuan, the total life can support 1,000 complete charging and discharging cycles (from 0% to 100%), and each complete cycle consumes 100 yuan, this trip from 35% to 31% consumes 4% of the power, which is equivalent to 0.04 complete cycles, then the battery life cost is 4 yuan; if in the ideal state, the vehicle is light load on flat road, 0-100km / h acceleration is 8 seconds, and climbing can stabilize at 80km / h, while the actual performance is that this heavy load climbing, 0-100km / h acceleration is 11 seconds, then the power performance loss is obvious, the acceleration is 3 seconds slower, and the power performance loss can be quantitatively calculated as 37.5%; if within 1 hour of driving, there are 3 times of obvious jerk during power switching, the ideal uniform speed is 60 decibels, and the actual climbing is 75 decibels, and the driving comfort score standard includes power smoothness: no jerk for 10 points, slight jerk for 7-8 points, obvious jerk for 4-6 points, and severe jerk for 1-3 points; noise and vibration: almost imperceptible for 10 points, slightly audible for 7-8 points, obvious interference for 4-6 points, and unbearable for 1-3 points, which can be quantified as a driving comfort score of 6 points (full score of 10 points), or a driving comfort loss of 40%. Thus, by determining the fuel consumption cost, battery life cost, power performance loss and driving comfort loss, precise data basis can be provided for subsequent optimization of energy management, improvement of vehicle cost performance, and extension of vehicle life, avoiding hidden losses caused by blind use.

[0050] S150, constructing a target function based on the fuel consumption cost, the battery life cost, the power performance loss, the driving comfort loss and the weight coefficient.

[0051] The weight coefficient is the importance proportion of the data. The weight coefficient includes a first weight coefficient, a second weight coefficient, a third weight coefficient and a fourth weight coefficient. The sum of the first weight coefficient, the second weight coefficient, the third weight coefficient and the fourth weight coefficient is 1 (or 100%). The weight coefficient is used to represent the degree of attention to the index data of different dimensions. The first weight coefficient is the weight coefficient corresponding to the fuel consumption cost. The second weight coefficient is the weight coefficient corresponding to the battery life cost. The third weight coefficient is the weight coefficient corresponding to the power performance loss. The fourth weight coefficient is the weight coefficient corresponding to the driving comfort loss.

[0052] Specifically, the four evaluation dimensions of fuel consumption cost, battery life cost, power performance loss and driving comfort loss are converted according to the respective weight coefficients and integrated into a unified comprehensive evaluation formula, i.e. the objective function, to finally measure the overall cost of vehicle operation with a numerical value, facilitating subsequent finding of the optimal vehicle energy management scheme. The objective function is essentially a weighted summation formula, which multiplies the four quantified indicators (fuel consumption cost, battery life cost, power performance loss and driving comfort loss) by their respective weight coefficients and then adds them to obtain a comprehensive cost value.

[0053] The objective function can be expressed as:

[0054] ;

[0055] The objective function can be expressed as:

[0056] S160, solving the objective function in the power feasible region to obtain the target range extender output power.

[0057] The power feasible region includes the range extender power feasible region and the battery power feasible region. The range extender is a vehicle-mounted power supply device for extending the cruising range of the range-extended electric vehicle. The range extender power feasible region is the power capability boundary of the range extender, i.e. the power range output by the range extender, which includes an upper limit and a lower limit. The upper limit is the maximum output power designed for the range extender, and the lower limit is the minimum stable power of the range extender. The battery power feasible region is the power range output by the battery, which includes output power and absorption power. The output power (positive power) is the maximum output power of the battery when supplying power to the vehicle, and the absorption power (negative power) is the power upper limit of the battery when recovering electric energy during vehicle deceleration. The target range extender output power is the final determined range extender output power.

[0058] Specifically, within the power feasible region, the power that the range extender cannot achieve is excluded, and only the power that can be achieved is selected. The fast gradient descent method is used to solve the objective function, and the power with the minimum comprehensive cost is selected by calculating the comprehensive cost corresponding to different powers. The target range extender output power can not only make the range extender operate normally (within the power feasible region), but also make the comprehensive cost of fuel consumption cost, battery life cost, power performance loss and driving comfort loss the lowest.

[0059] S170, determining a target battery output power based on the driving demand power and the target range extender output power.

[0060] The driving demand power is the total power required for the vehicle to travel at present. The target battery output power is the finally determined battery output power.

[0061] Specifically, the difference between the driving demand power and the target range extender output power is determined as the target battery output power.

[0062] S180, performing energy control on the target vehicle based on the target battery state of charge, the target range extender output power and the target battery output power.

[0063] Specifically, the three key targets, i.e. the target battery state of charge, the target range extender output power and the target battery output power, are determined as the control instructions of the vehicle energy management system, so as to coordinate the working states of the range extender and the battery, and ensure that the vehicle meets the driving demand, and is in the comprehensive optimal state of cost, life and experience.

[0064] Optionally, the target state data includes battery state data, range extender state data, vehicle state data and driving demand data; the battery state data includes a current battery state of charge, a battery current, a battery voltage and a battery temperature; the range extender state data includes a range extender output power, a fuel consumption rate and a working efficiency; the vehicle state data includes a vehicle speed, an acceleration and a slope; and the driving demand data includes a throttle pedal position, a brake pedal position and a driving mode.

[0065] The battery state data is data for reflecting the current working state, performance and remaining capacity of the battery. The range extender state data is data for reflecting the current running state of the range extender. The vehicle state data is data for reflecting the overall running condition, physical state and load condition of the vehicle. The driving demand data is data for reflecting the driving intention of the driver captured by a sensor. The current battery state of charge is the percentage of the remaining capacity of the battery. The battery current is the charging and discharging current size of the battery. The battery voltage is the supply voltage level of the battery. The battery temperature is the working temperature of the battery. The range extender output power is the size of the electric energy that can be output by the range extender per unit time. The fuel consumption rate is the amount of fuel consumed by the range extender per unit of electric energy output. The working efficiency is the proportion of the heat generated by the range extender by burning fuel that is converted into effective electric energy. The vehicle speed is the driving speed of the vehicle. The acceleration is the speed change of the vehicle. The slope is the inclination of the road surface on which the vehicle travels. The accelerator pedal position is the depth of the accelerator pedal, which is used to reflect the strength of the acceleration intention. The brake pedal position is the depth of the brake pedal, which is used to reflect the strength of the deceleration intention. The driving mode is the working mode of the vehicle, and the driving mode includes an economic mode, a standard mode, a sports mode and the like. For example, when the economic mode is selected, the vehicle causes the range extender to maintain the most fuel-efficient power interval, and the battery output is more gentle, and fuel consumption is preferentially reduced. When the sports mode is selected, the range extender increases the output power reserve, and the battery responds more quickly and has more powerful dynamics. The driving mode is used to reflect the driving preference. Under different driving modes, the response sensitivity of the vehicle to the accelerator and brake signals, and the power distribution logic of the range extender and the battery are different.

[0066] Optionally, based on the target state data, the working condition and the load state of the target vehicle are determined, including: based on the vehicle speed, the acceleration and the slope, the working condition characteristic data is determined; wherein the working condition characteristic data includes the average vehicle speed, the vehicle speed standard deviation, the acceleration distribution characteristic, the parking time proportion and the road slope change rate; based on a working condition recognition algorithm, the working condition characteristic data is processed to determine the working condition of the target vehicle; based on a vehicle dynamics equation, the vehicle state data and the driving demand data are processed to determine the load state of the target vehicle.

[0067] The working condition characteristic data is characteristic data reflecting a working condition. The average vehicle speed is an average driving speed in a driving time period. The vehicle speed standard deviation is used to reflect a fluctuation degree of the vehicle speed deviating from the average vehicle speed in the driving time period. The acceleration distribution characteristic is a frequency and a range of different accelerations (acceleration, deceleration) appearing in the driving time period. The parking time proportion is a proportion of a time in which the vehicle is stationary (i.e., the vehicle speed is 0) in the total time in the driving time period. The road slope change rate is a change frequency and a range of the slope in the driving time period. The working condition recognition algorithm is an algorithm for recognizing a working condition. The vehicle dynamics equation is a mathematical formula derived based on physical mechanics principles, and is used to calculate a total resistance to be overcome by the vehicle when driving, and to determine a load state, by using vehicle state data (vehicle speed, acceleration, slope, etc.) and driving demand data (throttle pedal position, brake pedal position). The working condition includes a city working condition, a high-speed working condition, a suburban working condition, a climbing working condition, and a downhill working condition. The load state includes an empty load, a medium load, and a heavy load.

[0068] Specifically, the target state data includes a vehicle speed, an acceleration, a slope, etc., the working condition characteristic data is calculated based on the real-time vehicle speed, the real-time acceleration, and the real-time slope, and the working condition characteristic data includes an average vehicle speed, a vehicle speed standard deviation, an acceleration distribution characteristic, a parking time proportion, and a road slope change rate; the working condition recognition algorithm is used to process the working condition characteristic data, and to determine the working condition of the target vehicle, i.e., the working condition recognition algorithm based on fuzzy logic is used to compare the working condition characteristic data with a working condition classification and determination template pre-stored in the system. The working condition classification and determination template includes: the city working condition module is frequent start-stop, the average vehicle speed is less than 30 km / h, and the parking time proportion is greater than 20%; the high-speed working condition template is continuous high speed, the average vehicle speed is greater than 80 km / h, and the speed standard deviation is less than 10 km / h; the suburban working condition template is a medium speed between the city and the high speed; the climbing working condition template is that the average slope is greater than 3%, and the duration is greater than 30 seconds; and the downhill working condition template is that the average slope is less than -3%, and the duration is greater than 30 seconds. For example, if the working condition characteristic data is consistent with "average vehicle speed 85 km / h, parking proportion 1%, and small vehicle speed fluctuation", it is determined that the working condition of the target vehicle is the high-speed working condition. Based on the vehicle dynamics equation, the total resistance (i.e., the load) to be overcome by the vehicle at present is calculated by combining the vehicle state data (such as the vehicle speed, the slope, etc.) and the driving demand data (such as the throttle pedal position, etc.), and the load is classified according to the standards of "less than 30% for the empty load, 30%-70% for the medium load, and 70% for the heavy load", so as to clearly determine the load state of the vehicle.

[0069] Optionally, the target state data of the target vehicle is obtained, including: collecting vehicle operation data of the target vehicle; and pre-processing the vehicle operation data to obtain the target state data of the target vehicle.

[0070] Specifically, through sensors, controllers, etc. on the target vehicle, vehicle operation data of the target vehicle is collected; the vehicle operation data is filtered and checked for validity, and abnormal data is removed to obtain target state data of the target vehicle. Filtering is to remove interference noise in the data. The validity check is used to remove completely invalid data. For example, a sensor failure reports a battery voltage of 500V (far beyond the normal range of 300-400V), which is obviously unreasonable and useless data and will be directly removed. Thus, through data preprocessing, the accuracy and reliability of the target state data are ensured.

[0071] The embodiment of the application determines a reasonable target battery state of charge according to the working condition and the load, and subsequent energy control keeps the battery in a safe interval all the time, avoiding the state of deep discharge, high temperature and high power that damages the battery; the target function integrates the fuel consumption cost, the battery life cost, the power performance loss and the driving comfort loss, and can also be flexibly adjusted through the weight coefficient, that is, by considering the economy, the power, the battery life and the driving comfort, the comprehensive optimization is realized through the weight self-adaptation, and then the target vehicle is controlled in energy through the determined target battery state of charge, the target range extender output power and the target battery output power, so that the energy utilization efficiency is maximized, the endurance mileage is prolonged, and the battery life and the real-time control requirement are considered at the same time under the premise of ensuring the power performance.

[0072] Figure 2 is a flowchart of a vehicle energy management method provided by the embodiment of the application, and the embodiment optimizes the "determination of the target battery state of charge of the target vehicle based on the working condition, the load state and the constraint condition", the "determination of the fuel consumption cost, the battery life cost, the power performance loss and the driving comfort loss based on the target state data", and the "solving of the target function in the power feasible region to obtain the target range extender output power" based on the above embodiments, and provides an optional implementation scheme. As shown in Figure 2 the method comprises:

[0073] S210, target state data of a target vehicle is obtained.

[0074] S220, the working condition and the load state of the target vehicle are determined based on the target state data.

[0075] S230, the target battery state of charge of the target vehicle is determined based on the working condition, the load state and the constraint condition.

[0076] S240, the fuel consumption cost, the battery life cost, the power performance loss and the driving comfort loss are determined based on the target state data.

[0077] S250, a target function is constructed based on the fuel consumption cost, the battery life cost, the power performance loss, the driving comfort loss and the weight coefficient.

[0078] S260, solving the target function in the power feasible region to obtain a target range extender output power.

[0079] S270, determining a target battery output power based on the driving demand power and the target range extender output power.

[0080] S280, performing energy control on the target vehicle based on the target battery state of charge, the target range extender output power and the target battery output power.

[0081] Optionally, the target battery state of charge of the target vehicle is determined based on the working condition, the load state and the constraint condition, and includes: determining the target battery state of charge of the target vehicle based on the working condition, the load state and a battery state of charge basic value under the constraint condition.

[0082] The battery state of charge basic value is a preset battery capacity reference value.

[0083] Specifically, the battery state of charge basic value is taken as a starting point, and the constraint condition of the battery is followed (for example, the target battery state of charge is limited in the range of 30%-70%, and the change rate of the target battery state of charge is not more than 2%), to finally determine a battery target capacity that meets the driving demand, protects the battery and reduces the comprehensive cost, i.e., the target battery state of charge (target SOC). For example, the battery state of charge basic value can be set to 50%; if the working condition is an urban working condition, then to enhance the regenerative braking capability; if the working condition is a high-speed working condition, then to optimize the range extender efficiency; if the working condition is a climbing working condition, then to reserve the climbing energy; if the working condition is a downhill working condition, then to reserve the regenerative space; if the load state is heavy load, then to enhance the power reserve; if the load state is empty load, then to reduce the battery load.

[0084] Optionally, it also includes determining the target battery state of charge of the target vehicle based on the working condition, the load state, the battery temperature and the constraint condition. For example, if the battery temperature is low, i.e., the battery temperature is less than 0 degrees Celsius, then to compensate for the performance decline at low temperature; if the battery temperature is high, i.e., the battery temperature is greater than 35 degrees Celsius, then to reduce the battery thermal load.

[0085] Optionally, based on the target state data, the fuel consumption cost, the battery life cost, the power performance loss and the driving comfort loss are determined, including: based on the fuel consumption rate, the range extender output power and the fuel price, the fuel consumption cost is determined; based on the battery current, the wear coefficient, the current stress index, the current battery state of charge and the battery temperature, the battery life cost is determined; based on the vehicle state data and the driving demand data, the driving demand power is determined; based on the driving demand power and the available power, the power performance loss is determined; based on the range extender output power, the driving comfort loss is determined.

[0086] Wherein, the fuel price is the price per liter of fuel. The wear coefficient is a preset parameter for measuring the anti-wear ability of the battery. The current stress index is the influence weight of the current on the battery wear, which is used to reflect the influence degree of the current size on the battery wear. The available power is the maximum dynamic upper limit that the vehicle can provide at present, and the available power is the sum of the range extender output power and the battery output power.

[0087] Specifically, based on the fuel consumption rate, the range extender output power and the fuel price, the fuel consumption cost is calculated through the calculation formula of the fuel consumption cost; based on the battery current, the wear coefficient, the current stress index, the current battery state of charge and the battery temperature, the battery life cost is calculated through the calculation formula of the battery life cost; based on the vehicle state data (such as speed, slope, etc.) and the driving demand data (such as the force of stepping on the accelerator or the brake), the total power required by the vehicle at present is calculated, which is the driving demand power; based on the driving demand power and the available power, the power performance loss is calculated through the calculation formula of the power performance loss; based on the range extender output power, the driving comfort loss is determined. For example, the range extender has a designed optimal comfort power interval, if the range extender output power is within the interval, it means that the engine speed is stable, the combustion is sufficient, the noise and vibration are minimal, and the driving comfort loss is minimal; if the range extender output power is lower than the interval, it means that the engine is unstable at low speed or frequent start-stop, the shaking, noise is large, and the driving comfort loss increases; if the range extender output power is higher than the interval, it means that the engine is running at high speed, the noise and vibration are soaring, and even resonance, the driving comfort loss increases significantly.

[0088] Optionally, the calculation formula of the fuel consumption cost can be expressed as:

[0089] ;

[0090] Wherein, J_fuel is the fuel consumption cost, m_fuel is the fuel consumption rate (unit: g / s), P_re is the range extender output power (unit: kW), price_fuel is the fuel price (unit: yuan / g).

[0091] Optionally, the calculation formula of the battery life cost can be expressed as:

[0092] ;

[0093] wherein J_battery is the battery life cost, k_wear is the wear coefficient, I_batt is the battery current (unit: A), n is the current stress index, n is usually taken as 1.5-2, is a function of SOC and T, SOC is the current battery state of charge, T is the battery temperature (unit: Celsius).

[0094] Optionally, the calculation formula of the power performance loss can be expressed as:

[0095] ;

[0096] wherein J_power is the power performance loss, P_demand is the driving demand power (unit: kW), P_available is the available power.

[0097] Optionally, the target range extender output power is obtained by solving the target function in the power feasible region, including: solving the target function in the power feasible region to obtain the first range extender output power corresponding to the minimum target function value; determining the battery state of charge deviation value based on the target battery state of charge and the current battery state of charge; determining the power correction amount based on the battery state of charge deviation value and the control parameter; determining the target range extender output power based on the power correction amount and the first range extender output power.

[0098] wherein the first range extender output power is the range extender output power obtained by solving the target function, which is the optimal range extender output power in the theoretical level. The battery state of charge deviation value is the difference between the target battery state of charge and the current battery state of charge. The control parameter is a pre-calibrated correction parameter. The control parameter includes proportional gain, integral gain and differential gain. The control parameter can be adjusted based on the working condition. The power correction amount is the power amplitude of the range extender output power adjustment.

[0099] Specifically, within the power feasible region (such as the output power of the range extender being limited between the minimum stable power and the maximum power, and the battery power not exceeding the charge and discharge limit), the target function is solved to obtain the first range extender output power corresponding to the minimum target function value; the difference obtained by subtracting the target battery state of charge from the current battery state of charge is taken as the battery state of charge deviation value; the power correction amount is determined based on the battery state of charge deviation value and the control parameter through the calculation formula of the power correction amount; and the target range extender output power is determined based on the power correction amount and the first range extender output power through the calculation formula of the target range extender output power. Thus, under the premise of meeting the driving demand, the lowest comprehensive cost, the longest battery life and the best driving experience are realized, so that the vehicle energy control is more intelligent and more suitable for actual use scenarios.

[0100] Optionally, the calculation formula of the power correction amount can be expressed as:

[0101] ;

[0102] Wherein, P_correction is the power correction amount (unit: kW), Kp is the proportional gain (unit: kW / %), Ki is the integral gain (unit: kW / %), Kd is the differential gain (unit: kW / %), and ΔSOC is the battery state of charge deviation value (unit: %).

[0103] Optionally, the calculation formula of the target range extender output power can be expressed as:

[0104] ;

[0105] Wherein, P_re_final is the target range extender output power (unit: kW), P_re_optimal is the first range extender output power (unit: kW), and P_correction is the power correction amount (unit: kW).

[0106] The embodiment of the application determines the target battery state of charge of the target vehicle based on the working condition, the load state and the battery state of charge basic value, sets the target battery state of charge more suitable for the scene, ensures that the battery works in a safe range, and avoids the safety risk of overcharging and overdischarging. The calculation logic of the fuel consumption cost, the battery life cost, the power performance loss and the driving comfort loss is clearly defined, and the accurate quantitative result can make the subsequent target function more truly reflect the actual situation, and the optimal range extender power solved is also more practical. Through power correction, the target range extender output power is more robust, the theoretical optimum and actual adaptation are considered, the overall logic closed loop is more rigorous, the energy control is more intelligent, and the energy control of the range-extended vehicle considers practicality, safety and economy.

[0107] Figure 3is a structural schematic diagram of a vehicle energy management device 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 and optimization of a range extended electric commercial vehicle. The device 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 device comprises: Figure 3

[0108] a data acquisition module 310 configured to acquire target state data of a target vehicle;

[0109] a working condition and load state determination module 320 configured to determine a working condition and a load state of the target vehicle based on the target state data;

[0110] a target battery state of charge determination module 330 configured to determine a target battery state of charge of the target vehicle based on the working condition, the load state and a constraint condition;

[0111] a cost loss determination module 340 configured to determine a fuel consumption cost, a battery life cost, a power performance loss and a driving comfort loss based on the target state data;

[0112] a function construction module 350 configured to construct a target function based on the fuel consumption cost, the battery life cost, the power performance loss, the driving comfort loss and a weight coefficient;

[0113] a target range extender output power determination module 360 configured to solve the target function in a power feasible region to obtain a target range extender output power;

[0114] a target battery output power determination module 370 configured to determine a target battery output power based on a driving demand power and the target range extender output power;

[0115] a vehicle control module 380 configured to perform energy control on the target vehicle based on the target battery state of charge, the target range extender output power and the target battery output power.

[0116] ​The embodiment of the application determines reasonable target battery state of charge according to the working condition and the load, and subsequent energy control keeps the battery in a safe interval all the time, avoiding the state of deep discharge, high temperature and high power, etc. which damages the battery. The target function integrates the fuel consumption cost, the battery life cost, the power performance loss and the driving comfort loss, and can be flexibly adjusted through the weight coefficient, that is, by considering the economy, the power performance, the battery life and the driving comfort, the comprehensive optimization is realized through the weight self-adaption, and then the target vehicle is controlled in energy through the determined target battery state of charge, the target range extender output power and the target battery output power, so that the energy utilization efficiency is maximized, the endurance mileage is prolonged, and the battery life and the real-time control requirement are considered at the same time.

[0117] Optionally, the target state data includes battery state data, range extender state data, vehicle state data and driving demand data; the battery state data includes current battery state of charge, battery current, battery voltage and battery temperature; the range extender state data includes range extender output power, fuel consumption rate and working efficiency; the vehicle state data includes vehicle speed, acceleration and slope; and the driving demand data includes accelerator pedal position, brake pedal position and driving mode.

[0118] Optionally, the working condition load determination module 320 includes:

[0119] The working condition characteristic data determination unit is configured to determine working condition characteristic data based on the vehicle speed, the acceleration and the slope; wherein the working condition characteristic data includes average vehicle speed, vehicle speed standard deviation, acceleration distribution characteristic, parking time proportion and road slope change rate.

[0120] The working condition recognition unit is configured to process the working condition characteristic data based on a working condition recognition algorithm to determine the working condition of the target vehicle.

[0121] The load determination unit is configured to process the vehicle state data and the driving demand data based on a vehicle dynamics equation to determine the load state of the target vehicle.

[0122] Optionally, the target battery state of charge determination module 330 is specifically configured to determine the target battery state of charge of the target vehicle based on the working condition, the load state and the battery state of charge basic value under the constraint condition.

[0123] Optionally, the cost loss determination module 340 includes:

[0124] The fuel consumption cost determination unit is configured to determine the fuel consumption cost based on the fuel consumption rate, the range extender output power and the fuel price.

[0125] A battery life cost determining unit is configured to determine a battery life cost based on a battery current, a wear coefficient, a current stress index, a current battery state of charge and a battery temperature;

[0126] A driving demand power determining unit is configured to determine a driving demand power based on vehicle state data and driving demand data;

[0127] A power performance loss determining unit is configured to determine a power performance loss based on the driving demand power and the available power;

[0128] A driving comfort loss determining unit is configured to determine a driving comfort loss based on the range extender output power.

[0129] Optionally, the target range extender output power determining module 360 comprises:

[0130] A first range extender output power determining unit is configured to solve the target function in the power feasible region to obtain a first range extender output power corresponding to a minimum target function value;

[0131] A battery state of charge deviation value determining unit is configured to determine a battery state of charge deviation value based on the target battery state of charge and the current battery state of charge;

[0132] A power correction amount determining unit is configured to determine a power correction amount based on the battery state of charge deviation value and a control parameter;

[0133] A target range extender output power determining unit is configured to determine a target range extender output power based on the power correction amount and the first range extender output power.

[0134] 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.

[0135] 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.

[0136] Figure 4A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0137] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0138] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0139] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as vehicle energy management methods.

[0140] In some embodiments, the vehicle energy management method can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 18. In some embodiments, parts or all of the computer program can be loaded and / or installed onto electronic device 10 via, e.g., ROM 12 and / or communication unit 19. When the computer program is loaded onto RAM 13 and executed by processor 11, one or more steps of the vehicle energy management method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the vehicle energy management method by other means, e.g., with the aid of firmware.

[0141] 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.

[0142] Computer programs implementing methods of the present 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] It should be understood that the various forms of flow shown above can be used to reorder, add or delete steps. For example, each step described in the present application can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which is not limited herein.

[0148] The above detailed description does not constitute a limitation on the scope of protection 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 scope of protection of the present application.

Claims

1. A vehicle energy management method, characterized in that, The method includes: Obtain the target status data of the target vehicle; Based on the target status data, the operating condition and load status of the target vehicle are determined; Based on the operating conditions, load status, and constraints, determine the target battery state of charge of the target vehicle. Based on the target state data, determine the fuel consumption cost, battery life cost, power performance loss, and driving comfort loss. An objective function is constructed based on the fuel consumption cost, battery life cost, power performance loss, driving comfort loss, and weighting coefficients. Within the power feasible region, the objective function is solved to obtain the target range extender output power; The target battery output power is determined based on the driving power demand and the target range extender output power. Energy control is performed on the target vehicle based on the target battery state of charge, the target range extender output power, and the target battery output power.

2. The method according to claim 1, characterized in that, The target status data includes battery status data, range extender status data, vehicle status data, and driving demand data; the battery status data includes the current battery state of charge, battery current, battery voltage, and battery temperature; the range extender status data includes the range extender output power, fuel consumption rate, and operating efficiency; the vehicle status data includes vehicle speed, acceleration, and gradient; and the driving demand data includes accelerator pedal position, brake pedal position, and driving mode.

3. The method according to claim 2, characterized in that, Determining the operating condition and load status of the target vehicle based on the target state data includes: Based on the vehicle speed, the acceleration, and the slope, operating condition characteristic data are determined; wherein, the operating condition characteristic data includes average vehicle speed, vehicle speed standard deviation, acceleration distribution characteristics, stopping time ratio, and road slope change rate; Based on the working condition recognition algorithm, the working condition feature data is processed to determine the working condition of the target vehicle. Based on the vehicle dynamics equations, the vehicle state data and the driving demand data are processed to determine the load state of the target vehicle.

4. The method according to claim 2, characterized in that, Determining the target battery state of charge of the target vehicle based on the operating conditions, load state, and constraints includes: Under constraints, the target battery state of charge of the target vehicle is determined based on the operating conditions, the load state, and the basic values ​​of the battery state of charge.

5. The method according to claim 2, characterized in that, The determination of fuel consumption cost, battery life cost, power performance loss, and driving comfort loss based on the target state data includes: The fuel consumption cost is determined based on the fuel consumption rate, the range extender output power, and the fuel price. The battery life cost is determined based on the battery current, wear coefficient, current stress index, current battery state of charge, and battery temperature. Based on the vehicle status data and the driving demand data, the driving demand power is determined; Based on the driving power demand and available power, determine the power performance loss; The loss of driving comfort is determined based on the output power of the range extender.

6. The method according to claim 2, characterized in that, Solving the objective function within the feasible power domain to obtain the target range extender output power includes: Within the feasible power domain, the objective function is solved to obtain the first range extender output power corresponding to the minimum objective function value; Based on the target battery state of charge and the current battery state of charge, determine the battery state of charge deviation value; Based on the battery state-of-charge deviation value and control parameters, the power correction amount is determined; The target range extender output power is determined based on the power correction amount and the output power of the first range extender.

7. A vehicle energy management device, characterized in that, The device includes: The data acquisition module is used to acquire the target status data of the target vehicle; The operating condition and load determination module is used to determine the operating condition and load status of the target vehicle based on the target status data. The target battery state of charge determination module is used to determine the target battery state of charge of the target vehicle based on the operating conditions, the load state, and the constraints. The cost loss determination module is used to determine fuel consumption cost, battery life cost, power performance loss, and driving comfort loss based on the target state data. The function construction module is used to construct an objective function based on the fuel consumption cost, the battery life cost, the power performance loss, the driving comfort loss, and weighting coefficients. The target range extender output power determination module is used to solve the objective function within the power feasible domain to obtain the target range extender output power. The target battery output power determination module is used to determine the target battery output power based on the driving power demand and the target range extender output power; The vehicle control module is used to perform energy control on the target vehicle based on the target battery state of charge, the target range extender output power, and the target battery output power.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, which is then 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 claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the vehicle energy management method according to any one of claims 1-6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the vehicle energy management method according to any one of claims 1-6.

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