Vehicle composite energy management method, device, equipment and storage medium

Abstract

The present invention discloses a vehicle composite energy management method, device, equipment and storage medium. The method determines whether a fuel cell system is turned on according to a preset switch control rule, and uses the vehicle power demand under different working conditions and the battery charge state of the power battery as the input result of the fuel cell system; when it is determined that the fuel cell system is turned on, the fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed by a sliding average filter to obtain the smoothed output power, and the fuel cell system is controlled to output the smoothed output power; when it is determined that the fuel cell system is turned off, the fuel cell system is controlled to be turned off, which can avoid overcharging of the power battery and large fluctuations in the output power of the fuel cell, can adapt to various complex working conditions, ensure the economy of hybrid vehicles, improve the durability of the fuel cell, and enhance the safety and life of the power battery.

Description

Technical Field

[0001] The present invention relates to the field of multi-energy powertrain control technology, and in particular to a vehicle composite energy management method, device, equipment and storage medium. Background Art

[0002] With the increasing scarcity of oil resources and increasingly stringent environmental regulations, countries around the world are vigorously developing new energy vehicles. As a truly zero-emission clean energy in the application link, hydrogen fuel cells have their unique advantages. Fuel cell vehicles can not only completely replace gasoline in terms of fuel, but also have the advantages of high energy conversion efficiency, short hydrogen refueling time, and long cruising range.

[0003] The energy management control strategy of fuel cell hybrid vehicles is a key technology of fuel cell control systems; the energy sources of fuel cell vehicles include fuel cells and energy storage, which can be power batteries or supercapacitors. The energy control algorithm coordinates and distributes the power output of fuel cells and energy storage in real time, reduces the load power fluctuation of the fuel cell engine, optimizes the engine's operating range and recovers braking energy to the greatest extent, thereby achieving optimal economy of the vehicle's power system.

[0004] The current fuel cell control method will reduce the durability and output efficiency of the fuel cell when the load fluctuates frequently and with large amplitudes. Under certain working conditions, the charging and discharging fluctuations of the power battery are too large, resulting in a shortened battery life and safety problems caused by overcharging and over-discharging. Summary of the invention

[0005] The main purpose of the present invention is to provide a vehicle composite energy management method, device, equipment and storage medium, aiming to solve the problems in the prior art where frequent and large-amplitude fluctuations in the load of the fuel cell reduce its durability and output efficiency, and under certain working conditions, the charging and discharging fluctuations of the power battery are too large, resulting in a shortened battery life and safety problems caused by overcharging and over-discharging.

[0006] In a first aspect, the present invention provides a vehicle composite energy management method, the vehicle composite energy management method comprising the following steps:

[0007] Determine whether the fuel cell system is turned on according to a preset switch control rule, and use the vehicle power demand and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system;

[0008] When it is determined that the fuel cell system is turned on, a fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed through a sliding average filter to obtain a smoothed output power, and the fuel cell system is controlled to output the smoothed output power;

[0009] When it is determined that the fuel cell system is shut down, the fuel cell system is controlled to be shut down.

[0010] Optionally, judging whether the fuel cell system is turned on according to a preset switch control rule, and taking the vehicle power requirement and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system, includes:

[0011] Determine whether the fuel cell system is turned on according to a preset switch control rule;

[0012] Real-time acquisition of the battery charge state of the power battery in the fuel cell hybrid power system of the current vehicle, and acquisition of the vehicle controller to calculate the vehicle power demand of the current vehicle under different working conditions;

[0013] The difference between the vehicle required power and the lower limit of the preset high-efficiency power range of the fuel cell hybrid power system is obtained, and the difference and the battery state of charge are used as input results of the fuel cell system.

[0014] Optionally, when determining that the fuel cell system is turned on, obtaining fuzzy output power through fuzzy control calculation, smoothing the input result through a sliding average filter to obtain smoothed output power, and controlling the fuel cell system to output the smoothed output power, comprises:

[0015] When determining that the fuel cell system is turned on, determining the fuzzy rules and the membership functions of the input and output quantities according to a preset fuzzy control strategy;

[0016] Obtaining the fuzzy output power corresponding to the input result according to the fuzzy rule and the membership function, wherein the fuzzy rule includes that the operating output power of the fuel cell when in operation is greater than the idle power, and the battery state of charge is within a preset reasonable range;

[0017] Smoothing the input result by a sliding average filter to obtain a smoothed output power;

[0018] The fuel cell system is controlled to output the smoothed output power.

[0019] Optionally, the fuzzy rule includes that the operating output power of the fuel cell is greater than the idle power, and the battery state of charge is within a preset reasonable range.

[0020] Optionally, acquiring the fuzzy output power corresponding to the input result according to the fuzzy rule and the membership function includes:

[0021] Optimizing the membership function to obtain an optimized objective function;

[0022] According to the fuzzy rule and the objective function, the fuzzy output power corresponding to the input result is obtained by the following formula:

[0023] Pfc_req1=Pfc_g1+(Pfc_g2-Pfc_g1)*K

[0024] Among them, Pfc_req1 is the fuzzy output power, Pfc_g1 is the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, Pfc_g2 is the required power of the whole vehicle, and K is the fuel cell output power proportional coefficient.

[0025] Optionally, optimizing the membership function to obtain an optimized objective function includes:

[0026] The particle swarm algorithm is used to optimize the membership function offline, and the optimized objective function is obtained by the following formula:

[0027]

[0028] Among them, min o bj(x) is the minimum value of the objective function, are the target values; w1 and w2 are the weight coefficients of the optimized target values; ΔSOC is the change in battery SOC; and T is the time of the entire cycle.

[0029] Optionally, the smoothing the input result by a sliding average filter to obtain a smoothed output power includes:

[0030] The input result is smoothed by a sliding average filter, and the smoothed output power is obtained by the following formula:

[0031]

[0032] Among them, N is the number of data contained in the sliding window; T is the sampling time; k is the time on the time axis; P fc_req1_T The output power of the fuel cell calculated by the fuzzy controller at time T.

[0033] In a second aspect, in order to achieve the above-mentioned object, the present invention further proposes a vehicle composite energy management device, the vehicle composite energy management device comprising:

[0034] A judgment module is used to judge whether the fuel cell system is turned on according to a preset switch control rule, and use the vehicle power demand and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system;

[0035] an output power determination module, for obtaining a fuzzy output power through fuzzy control calculation when determining that the fuel cell system is turned on, smoothing the input result through a sliding average filter to obtain a smoothed output power, and controlling the fuel cell system to output the smoothed output power;

[0036] The control module is used to control the fuel cell system to be shut down when it is determined that the fuel cell system is shut down.

[0037] In the third aspect, in order to achieve the above-mentioned purpose, the present invention also proposes a vehicle composite energy management device, which includes: a memory, a processor, and a vehicle composite energy management program stored in the memory and executable on the processor, and the vehicle composite energy management program is configured to implement the steps of the vehicle composite energy management method as described above.

[0038] In a fourth aspect, in order to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a vehicle composite energy management program is stored, and when the vehicle composite energy management program is executed by a processor, the steps of the vehicle composite energy management method as described above are implemented.

[0039] The vehicle composite energy management method proposed in the present invention determines whether the fuel cell system is turned on by preset switch control rules, and uses the vehicle power demand under different working conditions of the current vehicle and the battery charge state of the power battery as the input results of the fuel cell system; when it is determined that the fuel cell system is turned on, the fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed by a sliding average filter to obtain the smoothed output power, and the fuel cell system is controlled to output the smoothed output power; when it is determined that the fuel cell system is turned off, the fuel cell system is controlled to be turned off, and the fuel cell output power can be calculated according to the vehicle power demand under different operating conditions of the vehicle, with better continuity, avoiding overcharging of the power battery, having better adaptability to complex working conditions, and can improve the safety and life of the battery. The sliding average filter processing avoids large fluctuations in the fuel cell output power, ensures the economy of the hybrid vehicle, improves the durability of the fuel cell, and improves the safety and life of the power battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention;

[0041] Figure 2 A schematic diagram of a flow chart of a first embodiment of a vehicle composite energy management method according to the present invention;

[0042] Figure 3A flow chart of a composite energy management strategy for a fuel cell hybrid electric vehicle in a composite energy management method for a vehicle;

[0043] Figure 4 A schematic diagram of a flow chart of a second embodiment of a vehicle composite energy management method according to the present invention;

[0044] Figure 5 A schematic diagram of a flow chart of a third embodiment of a vehicle composite energy management method according to the present invention;

[0045] Figure 6 The output power efficiency characteristic curve of the fuel cell in the vehicle composite energy management method of the present invention;

[0046] Figure 7 A schematic diagram of fuzzy rules in the vehicle composite energy management method of the present invention;

[0047] Figure 8 A schematic diagram of the membership function in the vehicle composite energy management method of the present invention;

[0048] Fig. 9 A schematic diagram of switch control rules in the vehicle composite energy management method of the present invention;

[0049] Fig.10 It is a schematic diagram of sliding average filtering in the vehicle composite energy management method of the present invention;

[0050] Fig.11 This is a functional module diagram of the first embodiment of the vehicle composite energy management device of the present invention.

[0051] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0052] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0053] The solution of the embodiment of the present invention is mainly as follows: judging whether the fuel cell system is turned on or not by a preset switch control rule, taking the vehicle power demand under different working conditions of the current vehicle and the battery charge state of the power battery as the input result of the fuel cell system; when judging that the fuel cell system is turned on, obtaining the fuzzy output power by fuzzy control calculation, smoothing the input result by a sliding average filter, obtaining the smoothed output power, and controlling the fuel cell system to output the smoothed output power; when judging that the fuel cell system is turned off, controlling the fuel cell system to be turned off, being able to calculate the fuel cell output power according to the vehicle power demand under different operating conditions of the vehicle, having better continuity, avoiding overcharging of the power battery, having better adaptability to complex working conditions, and improving the safety and life of the battery, avoiding large fluctuations in the fuel cell output power by sliding average filtering, ensuring the economy of the hybrid vehicle, improving the durability of the fuel cell, and improving the safety and life of the power battery, solving the problem in the prior art that frequent and large fluctuations in the load of the fuel cell will reduce its durability and output efficiency, and the excessive change in the charging and discharging of the power battery under certain working conditions will lead to the problem of shortened battery life and safety problems caused by overcharging and over-discharging.

[0054] Reference Figure 1 , Figure 1 The figure is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention.

[0055] like Figure 1 As shown, the device may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed RAM memory, or it may be a stable memory (Non-Volatile Memory), such as a disk memory. The memory 1005 may optionally be a storage device independent of the aforementioned processor 1001.

[0056] Those skilled in the art will understand that Figure 1 The device structure shown in the figure does not constitute a limitation of the device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0057] like Figure 1As shown, the memory 1005 as a storage medium may include an operating device, a network communication module, a user interface module, and a vehicle composite energy management program.

[0058] The device of the present invention calls the vehicle composite energy management program stored in the memory 1005 through the processor 1001, and performs the following operations:

[0059] Determine whether the fuel cell system is turned on according to a preset switch control rule, and use the vehicle power demand and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system;

[0060] When it is determined that the fuel cell system is turned on, a fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed through a sliding average filter to obtain a smoothed output power, and the fuel cell system is controlled to output the smoothed output power;

[0061] When it is determined that the fuel cell system is shut down, the fuel cell system is controlled to be shut down.

[0062] The device of the present invention calls the vehicle composite energy management program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0063] Determine whether the fuel cell system is turned on according to a preset switch control rule;

[0064] Real-time acquisition of the battery charge state of the power battery in the fuel cell hybrid power system of the current vehicle, and acquisition of the vehicle controller to calculate the vehicle power demand of the current vehicle under different working conditions;

[0065] The difference between the vehicle required power and the lower limit of the preset high-efficiency power range of the fuel cell hybrid power system is obtained, and the difference and the battery state of charge are used as input results of the fuel cell system.

[0066] The device of the present invention calls the vehicle composite energy management program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0067] When determining that the fuel cell system is turned on, determining the fuzzy rules and the membership functions of the input and output quantities according to a preset fuzzy control strategy;

[0068] Obtaining the fuzzy output power corresponding to the input result according to the fuzzy rule and the membership function, wherein the fuzzy rule includes that the operating output power of the fuel cell when in operation is greater than the idle power, and the battery state of charge is within a preset reasonable range;

[0069] Smoothing the input result by a sliding average filter to obtain a smoothed output power;

[0070] The fuel cell system is controlled to output the smoothed output power.

[0071] The device of the present invention calls the vehicle composite energy management program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0072] The fuzzy rule includes that the operating output power of the fuel cell is greater than the idle power, and the battery state of charge is within a preset reasonable range.

[0073] The device of the present invention calls the vehicle composite energy management program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0074] Optimizing the membership function to obtain an optimized objective function;

[0075] According to the fuzzy rule and the objective function, the fuzzy output power corresponding to the input result is obtained by the following formula:

[0076] Pfc_req1=Pfc_g1+(Pfc_g2-Pfc_g1)*K

[0077] Among them, Pfc_req1 is the fuzzy output power, Pfc_g1 is the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, Pfc_g2 is the required power of the whole vehicle, and K is the fuel cell output power proportional coefficient.

[0078] The device of the present invention calls the vehicle composite energy management program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0079] The particle swarm algorithm is used to optimize the membership function offline, and the optimized objective function is obtained by the following formula:

[0080]

[0081] Among them, min o bj(x) is the minimum value of the objective function, are the target values; w1 and w2 are the weight coefficients of the optimized target values; ΔSOC is the change in battery SOC; and T is the time of the entire cycle.

[0082] The device of the present invention calls the vehicle composite energy management program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0083] The input result is smoothed by a sliding average filter, and the smoothed output power is obtained by the following formula:

[0084]

[0085] Among them, N is the number of data contained in the sliding window; T is the sampling time; k is the time on the time axis; P fc_req1_T The output power of the fuel cell calculated by the fuzzy controller at time T.

[0086] Through the above scheme, this embodiment determines whether the fuel cell system is turned on by preset switch control rules, and uses the vehicle power demand under different working conditions of the current vehicle and the battery charge state of the power battery as the input result of the fuel cell system; when it is determined that the fuel cell system is turned on, the fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed by a sliding average filter to obtain the smoothed output power, and the fuel cell system is controlled to output the smoothed output power; when it is determined that the fuel cell system is turned off, the fuel cell system is controlled to be turned off, and the fuel cell output power can be calculated according to the vehicle power demand under different operating conditions of the vehicle, with better continuity, avoiding overcharging of the power battery, having better adaptability to complex working conditions, and can improve the safety and life of the battery. The sliding average filter processing avoids large fluctuations in the fuel cell output power, ensures the economy of the hybrid vehicle, improves the durability of the fuel cell, and improves the safety and life of the power battery.

[0087] Based on the above hardware structure, an embodiment of the vehicle composite energy management method of the present invention is proposed.

[0088] Reference Figure 2 , Figure 2 It is a flow chart of the first embodiment of the vehicle composite energy management method of the present invention.

[0089] In a first embodiment, the vehicle composite energy management method comprises the following steps:

[0090] Step S10: determining whether the fuel cell system is turned on according to a preset switch control rule, and taking the vehicle power requirement and the battery charge state of the power battery under different current vehicle operating conditions as input results of the fuel cell system.

[0091] It should be noted that the preset switch control rule is a pre-set switch control rule that can determine whether the fuel cell system is turned on or off, and can use the vehicle's required power and the battery charge state of the power battery under different operating conditions as the input results of the fuel cell system.

[0092] Step S20: when it is determined that the fuel cell system is turned on, the fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed through a sliding average filter to obtain a smoothed output power, and the fuel cell system is controlled to output the smoothed output power.

[0093] It can be understood that when it is determined that the fuel cell system is turned on, the fuzzy output power can be obtained through fuzzy control calculation, and the input result can be smoothed by a sliding average filter to obtain a smoothed output power. The smoothed output power is the output power after the fuzzy output power is filtered, and the fuel cell system is controlled to output the smoothed output power.

[0094] In the specific implementation, the fuel cell system is turned on or off according to a pre-set switch control rule. If the fuel cell system is determined to be on, a fuel cell start-up signal is sent to the fuel cell system, and the output power calculated by the output fuzzy control is selected, that is, the fuzzy output power, and then smoothed through a sliding average filter to obtain the fuel cell output power, that is, the smoothed output power, which is output to the fuel cell system to control the fuel cell system to output the corresponding power.

[0095] Step S30: When it is determined that the fuel cell system is shut down, control the fuel cell system to shut down.

[0096] It should be understood that if the fuel cell system is determined to be shut down, a fuel cell shutdown signal is sent to the fuel cell system to control the fuel cell system to shut down, and the fuel cell output power is selected to be 0. The fuel cell is controlled to be shut down here to prevent the power battery from overcharging.

[0097] In the specific implementation, see Figure 3 , Figure 3 The flow chart of the hybrid energy management strategy of fuel cell hybrid electric vehicle in the hybrid energy management method of the vehicle is as follows: Figure 3 As shown in FIG. 1 , the composite energy management strategy of the fuel cell hybrid vehicle is as follows: the SOC of the power battery in the fuel cell hybrid system and the vehicle demand power Preq calculated by the vehicle controller are obtained in real time; the difference between the vehicle demand power Preq and the lower limit of the high-efficiency power zone of the fuel cell system and the power battery SOC are used as inputs; a fuel cell demand output power Pfc_req1 is obtained by using a fuzzy controller optimized in advance by a particle swarm algorithm; at the same time, the SOC of the power battery and the vehicle demand power Preq calculated by the vehicle controller are used as inputs; the fuel cell system is turned on or off by using a pre-set switch control rule; if the fuel cell system is determined to be turned on, a fuel cell turn-on signal is sent to the fuel cell system, and the output power Pfc_req1 calculated by the fuzzy control is selected for output; then, the sliding average filter is used for smoothing to obtain the fuel cell output power Pfc_req2, which is output to the fuel cell system to control the fuel cell system to output the corresponding power; if the fuel cell system is determined to be turned off, a fuel cell turn-off signal is sent to the fuel cell system to control the fuel cell system to turn off, and the fuel cell output power is selected to be 0.

[0098] Through the above scheme, this embodiment determines whether the fuel cell system is turned on by preset switch control rules, and uses the vehicle power demand under different working conditions of the current vehicle and the battery charge state of the power battery as the input result of the fuel cell system; when it is determined that the fuel cell system is turned on, the fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed by a sliding average filter to obtain the smoothed output power, and the fuel cell system is controlled to output the smoothed output power; when it is determined that the fuel cell system is turned off, the fuel cell system is controlled to be turned off, and the fuel cell output power can be calculated according to the vehicle power demand under different operating conditions of the vehicle, with better continuity, avoiding overcharging of the power battery, having better adaptability to complex working conditions, and can improve the safety and life of the battery. The sliding average filter processing avoids large fluctuations in the fuel cell output power, ensures the economy of the hybrid vehicle, improves the durability of the fuel cell, and improves the safety and life of the power battery.

[0099] Further, Figure 4 FIG. 1 is a flow chart of a second embodiment of the vehicle composite energy management method of the present invention. Figure 4 As shown, a second embodiment of the vehicle composite energy management method of the present invention is proposed based on the first embodiment. In this embodiment, the step S10 specifically includes the following steps:

[0100] Step S11: determining whether the fuel cell system is turned on according to a preset switch control rule.

[0101] It should be noted that the fuel cell system can be turned on or off by a pre-set switch control rule.

[0102] Step S12: acquiring the battery charge state of the power battery in the fuel cell hybrid power system of the current vehicle in real time, and obtaining the vehicle controller to calculate the vehicle power requirement of the current vehicle under different working conditions.

[0103] It can be understood that the battery state of charge (SOC) of the power battery in the fuel cell hybrid power system is obtained in real time and the vehicle controller calculates the vehicle power requirement of the current vehicle under different working conditions.

[0104] Step S13, obtaining the difference between the vehicle required power and the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, and using the difference and the battery state of charge as input results of the fuel cell system.

[0105] It should be understood that, by taking the difference between the vehicle's required power and the lower limit of the fuel cell system's high-efficiency power zone and the power battery SOC as input, the difference between the vehicle's required power and the lower limit of the preset high-efficiency power zone of the fuel cell hybrid system can be calculated, and then the difference and the battery state of charge can be used as input results of the fuel cell system.

[0106] Through the above scheme, this embodiment determines whether the fuel cell system is turned on according to the preset switch control rules; obtains the battery charge state of the power battery in the fuel cell hybrid power system of the current vehicle in real time, and obtains the vehicle controller to calculate the vehicle power demand of the current vehicle under different working conditions; obtains the difference between the vehicle power demand and the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, and uses the difference and the battery charge state as the input results of the fuel cell system. The fuel cell output power can be calculated according to the vehicle power demand under different operating conditions of the vehicle, with better continuity, avoiding overcharging of the power battery, better adaptability to complex working conditions, and improved battery safety and life.

[0107] Further, Figure 5 FIG. 1 is a flow chart of a third embodiment of the vehicle composite energy management method of the present invention. Figure 5 As shown, a third embodiment of the vehicle composite energy management method of the present invention is proposed based on the first embodiment. In this embodiment, the step S20 specifically includes the following steps:

[0108] Step S21: when determining that the fuel cell system is turned on, determining the fuzzy rules and the membership functions of the input and output quantities according to a preset fuzzy control strategy.

[0109] It should be noted that when determining whether the fuel cell system is turned on, the corresponding fuzzy rules and the membership functions of the input and output quantities may be determined according to a preset fuzzy control strategy.

[0110] In the specific implementation, the Mandani fuzzy control strategy can be used as the basic control strategy, with two inputs and one output. The fuzzy rules and the membership functions of the input and output quantities are determined according to the preset fuzzy control strategy. By setting the fuzzy rules and the membership functions of the input and output quantities, the output quantity is obtained from the two input quantities.

[0111] Step S22: Obtain the fuzzy output power corresponding to the input result according to the fuzzy rule and the membership function.

[0112] It can be understood that the fuzzy output power corresponding to the input result can be calculated and obtained through the fuzzy rules and the membership function.

[0113] Furthermore, the fuzzy rule includes that the operating output power of the fuel cell is greater than the idle power, and the battery state of charge is within a preset reasonable range.

[0114] In a specific implementation, the fuzzy control design principle is to ensure that the fuel cell output power is greater than its idle power when in operation in order to avoid affecting its durability when the fuel cell is in an idling state; to ensure that the fuel cell is operating in a high-efficiency area, the output power of the fuel cell should be in a high-efficiency area when in operation; to reduce the number of fuel cell starts and stops; and to keep the battery SOC within a reasonable range. Of course, the fuzzy rules can also be adjusted according to actual conditions, and this embodiment does not impose any restrictions on this.

[0115] Furthermore, the step S22 specifically includes the following steps:

[0116] Optimizing the membership function to obtain an optimized objective function;

[0117] According to the fuzzy rule and the objective function, the fuzzy output power corresponding to the input result is obtained by the following formula:

[0118] Pfc_req1=Pfc_g1+(Pfc_g2-Pfc_g1)*K

[0119] Among them, Pfc_req1 is the fuzzy output power, Pfc_g1 is the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, Pfc_g2 is the required power of the whole vehicle, and K is the fuel cell output power proportional coefficient.

[0120] It can be understood that the Mandani fuzzy control strategy can have two inputs and one output, that is, the difference ΔP (kW) between the vehicle demand power Preq and the lower limit of the high efficiency range Pfc_g1 can be used as one input, the power battery SOC can be used as another input, and the fuel cell output power proportional coefficient K can be used as the output K∈[0, 1]. A fuel cell demand output power Pfc_req1 can be obtained through a pre-set fuzzy controller.

[0121] It should be understood that see Figure 6 , Figure 6 is a characteristic curve diagram of the fuel cell output power efficiency in the vehicle composite energy management method of the present invention, such as Figure 6 As shown, according to the output power efficiency characteristics of the adopted fuel cell, the preset high-efficiency power area can be set to [Pfc_g1, Pfc_g2].

[0122] In the specific implementation, see Figure 7 , Figure 7 FIG. 1 is a schematic diagram of fuzzy rules in the vehicle composite energy management method of the present invention, as shown in FIG. Figure 7As shown, in the fuzzy rules, ΔP and SOC are input quantities, and the fuel cell output power proportional coefficient K is output quantity; the fuzzy subsets of ΔP, SOC and K are: {VS, S, M, B, VB}; in the fuzzy subsets, VS is extremely small; S is small; M is medium; B is large; and VB is extremely large.

[0123] See also Figure 8 , Figure 8 The schematic diagram of the membership function in the vehicle composite energy management method of the present invention is shown in FIG. The membership function of the input and output variables of the fuzzy controller is as follows: Figure 8 As shown, μ(ΔP), μ(SOC) and μ(K) are the membership degrees of ΔP, SOC and K respectively.

[0124] Furthermore, the step of optimizing the membership function to obtain an optimized objective function includes:

[0125] The particle swarm algorithm is used to optimize the membership function offline, and the optimized objective function is obtained by the following formula:

[0126]

[0127] Among them, min o bj(x) is the minimum value of the objective function, are the target values; w1 and w2 are the weight coefficients of the optimized target values; ΔSOC is the change in battery SOC; and T is the time of the entire cycle.

[0128] It should be understood that the particle swarm algorithm is used to perform offline parameter optimization of the membership function, and the optimized fuzzy controller is applied to the energy management strategy. The optimization goal is to minimize the equivalent hydrogen consumption of the whole vehicle and the change in battery SOC while ensuring the power of the vehicle. The optimized objective function can be obtained through the above formula.

[0129] In the specific implementation, you can set is 0.01, is 0.1, w1 and w2 are 0.5 and 0.5 respectively. The particle swarm optimization algorithm is used to optimize the membership function of the fuzzy controller according to the common operating conditions of the vehicle.

[0130] Step S23: smoothing the input result through a sliding average filter to obtain a smoothed output power.

[0131] It should be understood that the input result can be smoothed by a sliding average filter, thereby obtaining a smoothed output power.

[0132] Furthermore, the step S23 specifically includes the following steps:

[0133] The input result is smoothed by a sliding average filter, and the smoothed output power is obtained by the following formula:

[0134]

[0135] Among them, N is the number of data contained in the sliding window; T is the sampling time; k is the time on the time axis; P fc_req1_T The output power of the fuel cell calculated by the fuzzy controller at time T.

[0136] It is understandable that if Fig. 9 As shown, Fig. 9 This is a schematic diagram of the switch control rules in the vehicle composite energy management method of the present invention, see Fig. 9 , through the pre-set switch control rules, the fuel cell system is decided to be turned on or off. If the fuel cell system is determined to be turned on, the output power Pfc_req1 calculated by the fuzzy control is output to the sliding average filter for smoothing, and the fuel cell output power Pfc_req2 is obtained, which is output to the fuel cell system to control the fuel cell system to output the corresponding power. If the fuel cell system is determined to be turned off, a fuel cell shutdown signal is sent to the fuel cell system to control the fuel cell system to be turned off; Figure 8 In the table, FC_power is the output power of the fuel cell; FC_mode is the start / stop state of the fuel cell, 0 is off and 1 is on; P fc_req1 is the fuel cell output power calculated by fuzzy control; P_req is the vehicle required power; P_bat_max is the maximum output power of the power battery; SOC is the current SOC value of the power battery.

[0137] In the specific implementation, Fig.10 As shown, Fig.10 This is a schematic diagram of the sliding average filter in the vehicle composite energy management method of the present invention, see Fig.10 The output power Pfc_req1 calculated by the fuzzy controller is smoothed by a sliding average filtering algorithm to obtain the fuel cell output power Pfc_req2, which is characterized in that the sliding average filtering algorithm is equivalent to a sliding window with a fixed length of N, which slides along the discrete time series. Every time a sampling interval is slid, a new data enters the front of the window and an old data is removed from the back of the serial port. In this way, there are always N "latest" data in the window. As long as the N data in the window are arithmetic averaged after each sliding, a set of new sequences after sliding average filtering can be obtained, and its expression is the above formula.

[0138] Step S24: controlling the fuel cell system to output the smoothed output power.

[0139] It can be understood that after obtaining the fuzzy output power and the smooth output power, the fuel cell system can be controlled to output, that is, to output the smooth output power.

[0140] Through the above scheme, this embodiment determines the fuzzy rules and the membership function of the input and output quantities according to the preset fuzzy control strategy when judging that the fuel cell system is turned on; obtains the fuzzy output power corresponding to the input result according to the fuzzy rules and the membership function; smoothes the input result through a sliding average filter to obtain a smoothed output power; and controls the fuel cell system to output the smoothed output power. The sliding average filtering process can avoid large fluctuations in the fuel cell output power, thereby improving the safety and life of the battery.

[0141] Accordingly, the present invention further provides a vehicle composite energy management device.

[0142] Reference Fig.11 , Fig.11 This is a functional module diagram of the first embodiment of the vehicle composite energy management device of the present invention.

[0143] In the first embodiment of the vehicle composite energy management device of the present invention, the vehicle composite energy management device comprises:

[0144] The judgment module 10 is used to judge whether the fuel cell system is turned on according to a preset switch control rule, and uses the vehicle power demand and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system.

[0145] The output power determination module 20 is used to obtain the fuzzy output power through fuzzy control calculation when determining that the fuel cell system is turned on, smooth the input result through a sliding average filter to obtain the smoothed output power, and control the fuel cell system to output the smoothed output power.

[0146] The control module 30 is used to control the fuel cell system to shut down when it is determined that the fuel cell system is shut down.

[0147] The judgment module 10 is also used to judge whether the fuel cell system is turned on according to a preset switch control rule; to obtain the battery charge state of the power battery in the fuel cell hybrid power system of the current vehicle in real time, and to obtain the vehicle power demand calculated by the vehicle controller of the current vehicle under different working conditions; to obtain the difference between the vehicle power demand and the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, and to use the difference and the battery charge state as the input results of the fuel cell system.

[0148] The output power determination module 20 is also used to determine the fuzzy rules and the membership function of the input and output quantities according to the preset fuzzy control strategy when determining that the fuel cell system is turned on; obtain the fuzzy output power corresponding to the input result according to the fuzzy rules and the membership function; smooth the input result through a sliding average filter to obtain a smoothed output power; and control the fuel cell system to output the smoothed output power.

[0149] The output power determination module 20 is also used for the fuzzy rule including that the operating output power of the fuel cell when in operation is greater than the idle power, and the battery state of charge is within a preset reasonable range.

[0150] The output power determination module 20 is further used to optimize the membership function to obtain an optimized objective function; and obtain the fuzzy output power corresponding to the input result through the following formula according to the fuzzy rule and the objective function:

[0151] Pfc_req1=Pfc_g1+(Pfc_g2-Pfc_g1)*K

[0152] Among them, Pfc_req1 is the fuzzy output power, Pfc_g1 is the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, Pfc_g2 is the required power of the whole vehicle, and K is the fuel cell output power proportional coefficient.

[0153] The output power determination module 20 is also used to perform offline parameter optimization on the membership function using a particle swarm algorithm, and obtain the optimized objective function through the following formula:

[0154]

[0155] Among them, min o bj(x) is the minimum value of the objective function, are the target values; w1 and w2 are the weight coefficients of the optimized target values; ΔSOC is the change in battery SOC; and T is the time of the entire cycle.

[0156] The output power determination module 20 is further used to smooth the input result through a sliding average filter, and obtain the smoothed output power through the following formula:

[0157]

[0158] Among them, N is the number of data contained in the sliding window; T is the sampling time; k is the time on the time axis; P fc_req1_T The output power of the fuel cell calculated by the fuzzy controller at time T.

[0159] Among them, the steps implemented by each functional module of the vehicle composite energy management device can refer to the various embodiments of the vehicle composite energy management method of the present invention, and will not be repeated here.

[0160] In addition, an embodiment of the present invention further provides a storage medium, on which a vehicle composite energy management program is stored, and when the vehicle composite energy management program is executed by a processor, the following operations are implemented:

[0161] Determine whether the fuel cell system is turned on according to a preset switch control rule, and use the vehicle power demand and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system;

[0162] When it is determined that the fuel cell system is turned on, a fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed through a sliding average filter to obtain a smoothed output power, and the fuel cell system is controlled to output the smoothed output power;

[0163] When it is determined that the fuel cell system is shut down, the fuel cell system is controlled to be shut down.

[0164] Furthermore, when the vehicle composite energy management program is executed by the processor, the following operations are also implemented:

[0165] Determine whether the fuel cell system is turned on according to a preset switch control rule;

[0166] Real-time acquisition of the battery charge state of the power battery in the fuel cell hybrid power system of the current vehicle, and acquisition of the vehicle controller to calculate the vehicle power demand of the current vehicle under different working conditions;

[0167] The difference between the vehicle required power and the lower limit of the preset high-efficiency power range of the fuel cell hybrid power system is obtained, and the difference and the battery state of charge are used as input results of the fuel cell system.

[0168] Furthermore, when the vehicle composite energy management program is executed by the processor, the following operations are also implemented:

[0169] When determining that the fuel cell system is turned on, determining the fuzzy rules and the membership functions of the input and output quantities according to a preset fuzzy control strategy;

[0170] Acquire the fuzzy output power corresponding to the input result according to the fuzzy rule and the membership function;

[0171] Smoothing the input result by a sliding average filter to obtain a smoothed output power;

[0172] The fuel cell system is controlled to output the smoothed output power.

[0173] Furthermore, when the vehicle composite energy management program is executed by the processor, the following operations are also implemented:

[0174] The fuzzy rule includes that the operating output power of the fuel cell is greater than the idle power, and the battery state of charge is within a preset reasonable range.

[0175] Furthermore, when the vehicle composite energy management program is executed by the processor, the following operations are also implemented:

[0176] Optimizing the membership function to obtain an optimized objective function;

[0177] According to the fuzzy rule and the objective function, the fuzzy output power corresponding to the input result is obtained by the following formula:

[0178] Pfc_req1=Pfc_g1+(Pfc_g2-Pfc_g1)*K

[0179] Among them, Pfc_req1 is the fuzzy output power, Pfc_g1 is the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, Pfc_g2 is the required power of the whole vehicle, and K is the fuel cell output power proportional coefficient.

[0180] Furthermore, when the vehicle composite energy management program is executed by the processor, the following operations are also implemented:

[0181] The particle swarm algorithm is used to optimize the membership function offline, and the optimized objective function is obtained by the following formula:

[0182]

[0183] Among them, min o bj(x) is the minimum value of the objective function, are the target values; w1 and w2 are the weight coefficients of the optimized target values; ΔSOC is the change in battery SOC; and T is the time of the entire cycle.

[0184] Furthermore, when the vehicle composite energy management program is executed by the processor, the following operations are also implemented:

[0185] The input result is smoothed by a sliding average filter, and the smoothed output power is obtained by the following formula:

[0186]

[0187] Among them, N is the number of data contained in the sliding window; T is the sampling time; k is the time on the time axis; P fc_req1_T The output power of the fuel cell calculated by the fuzzy controller at time T.

[0188] Through the above scheme, this embodiment determines whether the fuel cell system is turned on by preset switch control rules, and uses the vehicle power demand under different working conditions of the current vehicle and the battery charge state of the power battery as the input result of the fuel cell system; when it is determined that the fuel cell system is turned on, the fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed by a sliding average filter to obtain the smoothed output power, and the fuel cell system is controlled to output the smoothed output power; when it is determined that the fuel cell system is turned off, the fuel cell system is controlled to be turned off, and the fuel cell output power can be calculated according to the vehicle power demand under different operating conditions of the vehicle, with better continuity, avoiding overcharging of the power battery, having better adaptability to complex working conditions, and can improve the safety and life of the battery. The sliding average filter processing avoids large fluctuations in the fuel cell output power, ensures the economy of the hybrid vehicle, improves the durability of the fuel cell, and improves the safety and life of the power battery.

[0189] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0190] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0191] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A vehicle composite energy management method, characterized in that: The vehicle composite energy management method comprises: Determine whether the fuel cell system is turned on according to a preset switch control rule, and use the vehicle power demand and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system; When it is determined that the fuel cell system is turned on, a fuzzy output power is obtained through fuzzy control calculation, the input result is smoothed through a sliding average filter to obtain a smoothed output power, and the fuel cell system is controlled to output the smoothed output power; When it is determined that the fuel cell system is shut down, controlling the fuel cell system to shut down; Wherein, when determining that the fuel cell system is turned on, obtaining fuzzy output power through fuzzy control calculation, smoothing the input result through a sliding average filter to obtain smoothed output power, and controlling the fuel cell system to output the smoothed output power, including: When determining that the fuel cell system is turned on, determining the fuzzy rules and the membership functions of the input and output quantities according to a preset fuzzy control strategy; Acquire the fuzzy output power corresponding to the input result according to the fuzzy rule and the membership function; Smoothing the input result by a sliding average filter to obtain a smoothed output power; Controlling the fuel cell system to output the smooth output power; Wherein, obtaining the fuzzy output power corresponding to the input result according to the fuzzy rule and the membership function includes: Optimizing the membership function to obtain an optimized objective function; According to the fuzzy rule and the objective function, the fuzzy output power corresponding to the input result is obtained by the following formula: Pfc_req1=Pfc_g1+(Pfc_g2-Pfc_g1)*K Wherein, Pfc_req1 is the fuzzy output power, Pfc_g1 is the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, Pfc_g2 is the required power of the whole vehicle, and K is the fuel cell output power proportional coefficient; The step of optimizing the membership function to obtain an optimized objective function includes: The particle swarm algorithm is used to optimize the membership function offline, and the optimized objective function is obtained by the following formula: Among them, min o bj(x) is the minimum value of the objective function, are the target values; w1 and w2 are the weight coefficients of the optimized target values; ΔSOC is the change of battery SOC; T is the time of the entire cycle condition. is the equivalent hydrogen consumption of the whole vehicle.

2. The vehicle composite energy management method according to claim 1, characterized in that: The method of judging whether the fuel cell system is turned on according to the preset switch control rule and taking the vehicle power demand and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system includes: Determine whether the fuel cell system is turned on according to a preset switch control rule; Real-time acquisition of the battery charge state of the power battery in the fuel cell hybrid power system of the current vehicle, and acquisition of the vehicle controller to calculate the vehicle power demand of the current vehicle under different working conditions; The difference between the vehicle required power and the lower limit of the preset high-efficiency power range of the fuel cell hybrid power system is obtained, and the difference and the battery state of charge are used as input results of the fuel cell system.

3. The vehicle composite energy management method according to claim 1, characterized in that: The fuzzy rule includes that the operating output power of the fuel cell is greater than the idle power, and the battery state of charge is within a preset reasonable range.

4. The vehicle composite energy management method according to claim 1, characterized in that: The step of smoothing the input result by a sliding average filter to obtain a smoothed output power includes: The input result is smoothed by a sliding average filter, and the smoothed output power is obtained by the following formula: Among them, N is the number of data contained in the sliding window; T is the sampling time; k is the time on the time axis; P fc_req1_T The output power of the fuel cell calculated by the fuzzy controller at time T.

5. A vehicle composite energy management device, characterized in that: The vehicle composite energy management device comprises: A judgment module is used to judge whether the fuel cell system is turned on according to a preset switch control rule, and use the vehicle power demand and the battery charge state of the power battery under different working conditions of the current vehicle as the input result of the fuel cell system; an output power determination module, configured to obtain a fuzzy output power through fuzzy control calculation when determining that the fuel cell system is turned on, smooth the input result through a sliding average filter to obtain a smoothed output power, and control the fuel cell system to output the smoothed output power; A control module, configured to control the fuel cell system to shut down when it is determined that the fuel cell system is shut down; The output power determination module is further used to determine the fuzzy rules and the membership function of the input and output quantities according to the preset fuzzy control strategy when determining that the fuel cell system is turned on; Acquire the fuzzy output power corresponding to the input result according to the fuzzy rule and the membership function; Smoothing the input result by a sliding average filter to obtain a smoothed output power; Controlling the fuel cell system to output the smooth output power; The output power determination module is also used to optimize the membership function to obtain an optimized objective function; According to the fuzzy rule and the objective function, the fuzzy output power corresponding to the input result is obtained by the following formula: Pfc_req1=Pfc_g1+(Pfc_g2-Pfc_g1)*K Wherein, Pfc_req1 is the fuzzy output power, Pfc_g1 is the lower limit of the preset high-efficiency power zone of the fuel cell hybrid power system, Pfc_g2 is the required power of the whole vehicle, and K is the fuel cell output power proportional coefficient; The output power determination module is also used to perform offline parameter optimization of the membership function using a particle swarm algorithm, and obtain the optimized objective function through the following formula: Among them, min o bj(x) is the minimum value of the objective function, are the target values; w1 and w2 are the weight coefficients of the optimized target values; ΔSOC is the change of battery SOC; T is the time of the entire cycle condition. is the equivalent hydrogen consumption of the whole vehicle.

6. A vehicle composite energy management device, characterized in that: The vehicle composite energy management device comprises: a memory, a processor and a vehicle composite energy management program stored in the memory and executable on the processor, wherein the vehicle composite energy management program is configured to implement the steps of the vehicle composite energy management method as described in any one of claims 1 to 4.

7. A storage medium, characterized in that: The storage medium stores a vehicle composite energy management program, which, when executed by a processor, implements the steps of the vehicle composite energy management method according to any one of claims 1 to 4.

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