A hybrid system energy management method and device considering battery hysteresis

Abstract

The present invention discloses a hybrid system energy management method and device considering battery hysteresis, including: S1: building a fuel cell hybrid power system model; S2: analyzing the voltage hysteresis of the fuel cell; S3: proposing an energy management strategy considering the voltage hysteresis of the fuel cell. The present invention realizes the local optimal output power within the power range that the fuel cell can output, effectively reduces the impact of the voltage hysteresis of the fuel cell, and effectively improves the economy. The voltage hysteresis of the fuel cell is studied through fuel cell bench test data, and the ohmic internal resistance value and the average time constant of the zero-state response under different load currents are analyzed respectively. The voltage hysteresis equation is introduced into the equivalent hydrogen consumption minimum strategy to accurately characterize the hysteresis power of the fuel cell when the load changes, and the constraints of the cost function are updated in real time. The equivalent hydrogen consumption minimum strategy considering the voltage hysteresis of the fuel cell is proposed and the effectiveness of the proposed strategy is verified under four working conditions.

Description

Technical Field

[0001] The invention relates to a hybrid system energy management method and device taking battery hysteresis into consideration, belonging to the technical field of power batteries. Background Art

[0002] The increasingly severe energy crisis and environmental problems have promoted the development of new energy vehicles. Among various new energy vehicles, fuel cell vehicles have longer driving range, higher energy density and shorter recharging time, and are regarded as the most promising clean energy vehicles in the future. However, when a single fuel cell is used as a vehicle power source, there are problems such as slow response speed and inability to recover braking energy. Therefore, fuel cell vehicles usually use a hybrid power system consisting of a fuel cell and an auxiliary power source. However, the existence of multiple power sources makes the energy flow of the power system complicated. In order to ensure reliable and efficient operation between the power sources, it is necessary to design a reasonable energy management strategy to distribute the energy of each power source.

[0003] According to different control principles, energy management strategies can be divided into rule-based, optimization-based and learning-based energy management strategies. Rule-based energy management strategies need to formulate a power allocation rule table based on experience, and determine the power allocation in combination with the current state parameters of the system. Common rule-based energy management strategies include deterministic rules and fuzzy rules. Optimization-based energy management strategies mainly use the state parameters of the hybrid power system to establish a cost function and solve the minimum value of the cost function under different constraints. Optimization-based energy management strategies are usually divided into global optimization strategies and local optimization strategies. Dynamic programming and minimum principle are commonly used in global optimization-based energy management strategies. Energy management strategies based on local optimization include equivalent hydrogen consumption minimum strategy, model predictive control, etc. In recent years, with the development of artificial intelligence technology, learning-based strategies have gradually become a research hotspot in the field of fuel cell energy management. At present, they can be divided into two categories: neural network-based and reinforcement learning-based.

[0004] The rule-based energy management strategy is limited by existing experience and knowledge, and it is difficult to achieve the optimal control effect. The learning-based energy management strategy requires a large amount of training data and training time. When the amount of data is small or the training time is limited, it is difficult to ensure a good control effect. In contrast, the energy management strategy based on global optimization can achieve global optimal economy, but is not suitable for real-time control. The energy management strategy based on local optimization has a faster response speed in real-time control and can find the optimal solution in a local range. In addition, compared with the rule-based and learning-based strategies, it has lower requirements for engineering experience and training data. Among the energy management strategies based on local optimization, the equivalent hydrogen consumption minimum strategy is widely used. Its core idea is to convert the electric energy consumption of the power battery into equivalent hydrogen consumption, and to achieve energy distribution with the goal of minimizing the total equivalent hydrogen consumption. At present, the research on the equivalent hydrogen consumption minimum strategy focuses on two aspects. First, by increasing the adaptability of the equivalent hydrogen consumption coefficient, the economy of the hybrid system is improved as a single optimization goal. Second, the economy and durability of the hybrid system are improved as multiple optimization goals.

[0005] In summary, no matter the research object is a single optimization target or multiple optimization targets, it is limited to the static model of the fuel cell and ignores the intrinsic characteristics of the fuel cell. When the load changes rapidly, the fuel cell will not be able to work at the optimal power output point in time due to the existence of hysteresis, which will have a negative impact on the economy of the hybrid system. Summary of the invention

[0006] Purpose of the invention: In view of the deficiencies in the prior art, the present invention provides a hybrid system energy management method and device taking battery hysteresis into consideration. The present invention achieves local optimal output power within the power range that the fuel cell can output by proposing a hybrid system energy management method taking battery hysteresis into consideration, thereby effectively reducing the impact of the fuel cell voltage hysteresis and effectively improving the economy.

[0007] Technical solution: A hybrid system energy management method considering battery hysteresis, comprising the following steps:

[0008] S1: Construction of fuel cell hybrid system model, including powertrain system construction, fuel cell model construction, power battery model construction, and drive motor model construction;

[0009] S2: Based on the fuel cell hybrid system model built in S1, analyze the voltage hysteresis of the fuel cell;

[0010] S201: Analyze the voltage characteristics of the fuel cell and measure the ohmic internal resistance value;

[0011] S202: based on the result of S201, obtaining the output voltage and actual output power of the fuel cell after the current changes load, specifically including fitting the hysteresis voltage process of the fuel cell, obtaining the time constant τ according to the fitting result, and obtaining the load addition and subtraction hysteresis equation according to the fitting result and the time constant, so as to obtain the output voltage and actual output power of the fuel cell after the current changes load;

[0012] S3: Based on the results of S1 and S2, an energy management strategy considering the voltage hysteresis of the fuel cell is proposed;

[0013] S301: Ensure that the hybrid power system meets the power required by the load through the control principle of the equivalent hydrogen consumption minimum strategy, and quantitatively analyze the impact of the fuel cell voltage hysteresis on power distribution;

[0014] S302: Based on the control principle of the equivalent hydrogen consumption minimum strategy in S301, an energy management strategy considering the voltage hysteresis of the fuel cell is proposed;

[0015] S303: Verify the effectiveness of the energy management strategy considering the fuel cell voltage hysteresis.

[0016] Preferably, the powertrain system is constructed as follows:

[0017] Choose to build a hybrid system by connecting fuel cells and power batteries in parallel. The fuel cells mainly provide the power required for the vehicle to travel smoothly, while the power batteries are used to alleviate power peaks and valleys.

[0018] During driving, the driving resistance includes the wheel rolling resistance F f , slope resistance F i , air resistance F w , acceleration resistance F a , the calculation formulas of each resistance are as follows:

[0019]

[0020] According to the force balance relationship, the driving force F of the vehicle t The calculation formula is as follows:

[0021] F t =F f +F i +F w +F a (10)

[0022] The required power of DC bus P load It can be derived from the vehicle longitudinal dynamics model, and the calculation formula is as follows:

[0023]

[0024] In the formula, Ft is the driving force, η t is the transmission system efficiency, η m is the motor efficiency, v is the vehicle speed, m is the total mass, f is the rolling coefficient, Cd is the air resistance coefficient, A is the frontal area, g is the acceleration of gravity, α is the angle corresponding to the road slope, a is the acceleration, and δ is the rotation mass conversion factor.

[0025] Preferably, the fuel cell model is constructed as follows:

[0026] Fuel cells require auxiliary devices to maintain their normal operation, and these auxiliary devices will also consume part of the power generated by the stack; therefore, the output power of the fuel cell system is shown as follows:

[0027] P fcs =P stack -P aux (4)

[0028] Where P stack is the fuel cell stack output power, P aux To consume power for auxiliary devices;

[0029] The current of the fuel cell is related to the reaction rate of hydrogen and oxygen. The hydrogen consumption rate is calculated by the current:

[0030]

[0031] In the formula, is the hydrogen consumption rate, N cell is the number of fuel cell cells, is the molar mass of hydrogen, is the number of electrons in the hydrogen molecule, F is the Faraday constant, I stack is the fuel cell stack current;

[0032] Given the hydrogen consumption rate, the fuel cell system efficiency is the ratio of the fuel cell system output power to the power that can be generated when consuming hydrogen:

[0033]

[0034] Where η fcs is the fuel cell system efficiency, P fcs is the fuel cell system power, Hydrogen has a low calorific value.

[0035] Preferably, the power battery model is constructed as follows:

[0036] Ignoring the effects of temperature and aging on the power battery, the internal resistance model of the power battery is shown in equations (7)-(9):

[0037] U bat =U OCV -I b R b (12)

[0038]

[0039]

[0040] Where U bat is the terminal voltage of the power battery, U OCV is the open circuit voltage of the power battery, I b is the power battery current, R b is the internal resistance of the power battery, P bat is the power of the power battery;

[0041] Power BatteryU OCV and R b There is a certain correlation with the state of charge SOC; the SOC is calculated using the ampere-hour integration method, which is expressed as follows:

[0042]

[0043] Among them, Q max is the maximum capacity of the power battery, and Δt is the step length.

[0044] Preferably, the driving motor model is constructed as follows:

[0045] Establish a static efficiency map, and build a drive motor model based on the static efficiency map: The working efficiency of the drive motor is a function of the current torque and speed, and the relationship is as follows:

[0046] η mot =f m (T mot ,n mot ) (16)

[0047] Where η mot is the motor efficiency, T mot is the motor torque, n mot is the motor speed, f m (·) is the corresponding efficiency lookup function.

[0048] Preferably, the S201 is specifically:

[0049] The fuel cell voltage is expressed as follows:

[0050] U cell =E nernst -U act -U ohm -U con(12)

[0051] U stack =N cell U cell (13)

[0052] Where U cell is the single cell voltage, E nernst is the Nernst voltage, U act is the activation loss voltage, U ohm is the ohmic loss voltage, U con is the concentration loss voltage, U stack is the stack voltage, N cell is the number of single battery cells;

[0053] The fuel cell stack output power can be calculated using the following formula:

[0054] P stack =U stack I stack (14)

[0055] Where P stack is the fuel cell stack output power, I stack is the stack current;

[0056] When the load current changes transiently, the voltage of the fuel cell is flexible and does not change immediately. It first undergoes a sudden change and then slowly reaches a stable value. After analysis, the sudden change of voltage is mainly caused by the ohmic loss voltage. The ohmic loss voltage satisfies Ohm's law, as shown in formula (15):

[0057] U ohm =I stack R ohm (15)

[0058] In the formula, R ohm is the ohmic internal resistance;

[0059] The working current of the fuel cell is made to step by the electronic load, the fuel cell current step point is set, and the corresponding voltage change is recorded; then, the voltage rapid change part ΔU is calculated by formula (16): ohm The ratio between the current step value ΔI and the ohmic internal resistance R is obtained. ohm ;

[0060]

[0061] Preferably, the S202 is specifically:

[0062] Based on the results of S201, when the external current changes transiently, the voltage of the fuel cell will produce a transient value ΔU ohm, then the voltage will slowly tend to a stable state. This gentle voltage change process is consistent with the change trend of the zero-state response curve of the first-order RC circuit. Therefore, the zero-state response equation of the first-order RC circuit is used to fit this gentle voltage change process, as shown in formula (17):

[0063] U c (t) = U s (1-e -t / t ) (17)

[0064] Where U c (t) is the voltage across the capacitor at time t, U s is the stable value of the voltage across the capacitor, t represents time, and τ is the time constant;

[0065] Based on equation (17) and the actual change of the fuel cell voltage, it can be obtained:

[0066] △U del =U stea -(U k-1 -△U ohm ) (18)

[0067] U t (t)=△U del (1-e -t / t ) (19)

[0068] In the formula, ΔU del is the hysteresis voltage of the fuel cell when the current changes with the load, U stea is the stable voltage after the current changes load, U k-1 is the stable voltage before the current changes load, ΔU ohm The voltage rapid change part caused by the ohmic internal resistance, U t (t) is the output voltage at time t after the current load changes;

[0069] According to the voltage data obtained in S201, the gentle voltage change process at the current step point is fitted according to formula (19) to obtain the time constant τ value corresponding to the minimum voltage fitting error, that is, the best fitting result. According to the time constant τ values ​​at different current step points, the average τ is selected. avg ;

[0070] According to the steady process of voltage change during current loading in S201, it is known that when the fuel cell load current decreases, its response speed is significantly faster than when the load increases. If the time constant during current reduction is set to the same value as that during current loading, it will not exceed the dynamic response capability of the fuel cell; therefore, the same time constant is selected during loading and unloading; combined with the actual change trend of the fuel cell voltage during load reduction and the zero-state response equation of the first-order RC circuit, the voltage fitting equation during load reduction is obtained as follows:

[0071] U t (t)=△U del e -t / t (20)

[0072] Therefore, by using equations (19) and (20) and combining the voltage at the previous moment, the output voltage that the fuel cell system can reach after the load current jumps t seconds later is calculated; by multiplying it with the current value after the step, the actual output power of the fuel cell system can be obtained, which is:

[0073] P load,act =U t (t)I (21)

[0074] Where I is the current after the step.

[0075] Preferably, the S301 is specifically:

[0076] In the equivalent hydrogen consumption minimization strategy, the state variable is set to the power battery SOC, and the control variable of the optimization problem is set to the output power P of the fuel cell. fcs ; Therefore, the energy distribution problem of the fuel cell hybrid system can be transformed into:

[0077] minC total =min(C fcs +κC bat ) (twenty two)

[0078] In the formula, C total is the total equivalent hydrogen consumption, C fcs is the direct hydrogen consumption of the fuel cell system, C bat is the indirect equivalent hydrogen consumption of the power battery, κ is the compensation coefficient related to the power battery SOC; where C fcs =cP fcs , c is obtained by fitting the fuel cell bench experimental data;

[0079] In normal operation, the energy source of a fuel cell hybrid vehicle is the fuel cell system; therefore, when evaluating the economic performance of the vehicle, it is necessary to convert the power consumed by the power battery into equivalent hydrogen consumption. The equivalent hydrogen consumption C batThe calculation is as follows:

[0080]

[0081] Where P bat is the power battery output power, C fc,avg is the average hydrogen consumption of the fuel cell, η chg,avg is the average charging efficiency of the power battery, P fc,avg is the average power of the fuel cell, η dis is the power battery discharge efficiency, η chg is the power battery charging efficiency, η dis,avg is the average discharge efficiency of the power battery;

[0082] During the operation of the power battery, the calculation formulas for the real-time charging efficiency and the real-time discharging efficiency are as follows:

[0083]

[0084] In the formula, R dis is the internal resistance of the power battery during discharge, R chg is the internal resistance of the power battery when charging, U OCV is the open circuit voltage of the power battery;

[0085] In order to ensure that the power battery SOC works within a reasonable range and prevent the power battery from being overcharged or over-discharged, it is necessary to introduce a compensation coefficient κ related to the power battery SOC; the compensation coefficient κ is expressed as:

[0086]

[0087] In the formula, μ is the balance coefficient, SOC L is the lower limit of the power battery SOC, SOC H The upper limit of the power battery SOC;

[0088] In order to ensure that the hybrid system can meet the power required by the load and ensure the normal operation of the entire system, the following constraints need to be considered when solving the optimization problem:

[0089]

[0090] Where P load is the load power demand, P fcs is the fuel cell system power, P bat is the power of the power battery, P bat,min is the minimum output power of the power battery, P bat,max is the maximum output power of the power battery, P fcs,max is the maximum output power of the fuel cell system, △P fcs,minis the minimum power variation range of the fuel cell system, △P fcs,max is the maximum power variation range of the fuel cell system;

[0091] In order to quantitatively analyze the influence of fuel cell voltage hysteresis on power distribution, n current step points are selected to analyze the difference between the actual output power and the expected output power of the fuel cell, so as to calculate the power hysteresis rate; the power hysteresis rate is calculated as follows:

[0092]

[0093] Where L is the power hysteresis rate, P tar is the fuel cell power at the target current load when stable, P inst

[0094] is the output power that the fuel cell can achieve after the current step occurs t seconds, ΔP L It is the difference between the fuel cell power when it is stable under the target current load and the fuel cell power when it is stable under the starting current load.

[0095] Preferably, the S302 is specifically:

[0096] Based on the S301 equivalent hydrogen consumption minimum strategy, that is, the above formula (22-26), the fuel cell voltage hysteresis equation, that is, the above formula (20), is proposed to accurately describe the voltage hysteresis phenomenon of the fuel cell, so as to dynamically adjust the constraint condition of the cost function, that is, the above formula (26), to optimize the output power of the fuel cell; the specific solution process of the improved equivalent hydrogen consumption minimum strategy is:

[0097] According to the vehicle speed V at time k act (k) and acceleration a act (k), the load demand power P at time k is calculated by the above formula (3) load,act (k):

[0098]

[0099] According to the equivalent hydrogen consumption minimum strategy, that is, the above formula (22-26), according to the actual load power demand P load,act (k) Perform energy distribution and calculate the expected power P of the fuel cell system at time k fcs,tar (k) specifically:

[0100] minC total =min(C fcs +κC bat )

[0101] C fcs =cP fcs,tar(k)

[0102]

[0103] P load,act (k) = P fcs,tar(k) +P bat

[0104] Combined with the voltage hysteresis equation, that is, the above formula (20), the fuel cell cost function is updated to solve the constraint condition, that is, the fuel cell output power range in the above formula (26), which is 0 to the maximum output power P of the fuel cell system when loaded fcs,max , when the load is reduced, it is 0 to the minimum output power P of the fuel cell system fcs,min , as follows:

[0105] U t (t)=△U del e -t / t

[0106]

[0107] According to the actual load power required at time k, P load,act (k) Energy distribution, that is, the above formula (22-26), solves the optimal power P that the fuel cell can achieve at time k fcs,act (k) specifically:

[0108] minC total =min(C fcs +κC bat )

[0109] C fcs =cP fcs,act (k)

[0110]

[0111] P load,act (k) = P fcs,act(k) +P bat .

[0112] A device for a hybrid system energy management method considering battery hysteresis includes a data acquisition module, a model building module, a control optimization module, and an energy management module.

[0113] The data acquisition module is used to extract the main relevant parameters of the whole vehicle, the relevant parameters of the fuel cell, the relevant parameters of the power battery, the relevant parameters of the drive motor, the speed and acceleration parameters;

[0114] The model building module is used to establish a fuel cell model by using the relationship between the hydrogen consumption rate and the efficiency of the fuel cell system; to establish a power battery model by using the relationship between parameters such as the battery open circuit voltage and internal resistance; and to establish a drive motor model by using a static efficiency MAP diagram;

[0115] The control optimization module is used to calculate the required load power based on the data in the data acquisition module, and then distribute the energy according to the equivalent hydrogen consumption minimum strategy to calculate the expected power of the fuel cell; based on the calculated expected power of the fuel cell, considering the hysteresis of the fuel cell, a fuel cell voltage hysteresis equation is proposed, so as to dynamically adjust the constraint conditions of the cost function to optimize the output power of the fuel cell;

[0116] The energy management module is used to distribute energy based on the optimized fuel cell output power and the required load power according to the equivalent hydrogen consumption minimum strategy, and calculate the optimal power that the fuel cell can achieve.

[0117] This device fully considers the hysteresis of the fuel cell and aims to solve the problem that when the load changes rapidly, the fuel cell cannot work at the optimal power output point in time due to the existence of voltage hysteresis, so as to make the energy management strategy more in line with the dynamic performance of the fuel cell and further improve the economy and durability.

[0118] Beneficial effects: The present invention can achieve local optimal output power within the power range that the fuel cell can output, effectively reducing the impact of the voltage hysteresis of the fuel cell, and effectively improving the economy. The voltage hysteresis of the fuel cell was studied through fuel cell bench test data, and the ohmic internal resistance value and the average time constant of the zero-state response under different load currents were analyzed respectively. On the basis of the existing fuel cell static efficiency model, the voltage hysteresis equation is introduced into the equivalent hydrogen consumption minimum strategy, which accurately describes the hysteresis power of the fuel cell when the load changes, and updates the constraints of the cost function in real time. An equivalent hydrogen consumption minimum strategy considering the voltage hysteresis of the fuel cell is proposed and the effectiveness of the proposed strategy is verified under four working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0119] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0120] Figure 1 is a flow chart of the method of the present invention;

[0121] Figure 2A hybrid power system configuration in which a fuel cell and a power battery are connected in parallel;

[0122] Figure 3 is a graph of hydrogen consumption rate and fuel cell system efficiency;

[0123] Figure 4 It is the relationship diagram between battery model parameters and SOC;

[0124] Figure 5 It is the electrode static efficiency MAP diagram;

[0125] Figure 6 This is the principle diagram of the current step method;

[0126] Figure 7 (ab) are fuel cell bench test data; (a) is the overall operation data diagram of current and voltage; (b) is the polarization characteristic curve diagram;

[0127] Figure 8 It is the ohmic internal resistance diagram under different load currents;

[0128] Fig. 9 It is the zero-state response curve of the first-order RC circuit;

[0129] Fig.10 (af) are time constant fitting diagrams under different methods; (a) is number 1; (b) is number 2; (c) is number 3; (d) is number 4; (e) is number 5; (f) is number 6;

[0130] Fig.11 The improved ECMS flow chart considering the voltage hysteresis of the fuel cell;

[0131] Fig.12 (ad) are the verification data diagrams of four working conditions, among which (a) is the high-speed working condition; (b) is the medium-speed working condition; (c) is the low-speed working condition; (d) is the comprehensive working condition;

[0132] Fig.13 (ad) are simulation result analysis diagrams under high-speed conditions; (a) is a fuel cell power comparison diagram before and after the ECMS strategy is improved; (b) is a selected segment (I) from Figure (a); (c) is a selected segment (II) from Figure (a); (d) is a SOC comparison diagram before and after the ECMS strategy is improved;

[0133] Fig.14 (ad) are simulation result analysis diagrams under medium speed conditions; (a) is a fuel cell power comparison diagram before and after the ECMS strategy is improved; (b) is a selected segment (I) from Figure (a); (c) is a selected segment (II) from Figure (a); (d) is a SOC comparison diagram before and after the ECMS strategy is improved;

[0134] Fig.15 (ab) are analysis diagrams of simulation results under low-speed conditions, where (a) is the fuel cell power comparison before and after the improved ECMS strategy; (b) is the SOC comparison before and after the improved ECMS strategy;

[0135] Fig.16 (ad) are analysis diagrams of simulation results under comprehensive working conditions, where (a) is a comparison diagram of fuel cell power before and after the improved ECMS strategy; (b) is a fragment (Ⅰ) selected from Figure (a); (c) is a fragment (Ⅱ) selected from Figure (a); (d) is a comparison diagram of SOC before and after the improved ECMS strategy. DETAILED DESCRIPTION

[0136] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0137] In the description of the present invention, it is necessary to understand that the terms "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0138] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0139] like Figure 1 As shown, a hybrid system energy management method considering battery hysteresis includes the following steps: S1: fuel cell hybrid power system model construction, including powertrain system construction, fuel cell model construction, power battery model construction, and drive motor model construction;

[0140] The powertrain system is specifically constructed as follows:

[0141] like Figure 2 As shown, a fuel cell and a power battery are selected in parallel to construct a hybrid power system. The fuel cell mainly provides the power required for the vehicle to drive smoothly, and the power battery is used to alleviate the power peak and valley. The main parameters of the powertrain are shown in Table 1.

[0142] Table 1 Main parameters of powertrain

[0143]

[0144]

[0145] During driving, the driving resistance includes the wheel rolling resistance F f , slope resistance F i , air resistance F w , acceleration resistance F a , the calculation formulas of each resistance are as follows:

[0146]

[0147] According to the force balance relationship, the driving force F of the vehicle t The calculation formula is as follows:

[0148] F t =F f +F i +F w +F a (18)

[0150] The required power of DC bus P load It can be derived from the vehicle longitudinal dynamics model, and the calculation formula is as follows:

[0151]

[0152] In the formula, F t is the driving force, η t is the transmission system efficiency, η m is the motor efficiency, v is the vehicle speed, m is the total mass, f is the rolling coefficient, Cd is the air resistance coefficient, A is the frontal area, g is the acceleration of gravity, α is the angle corresponding to the road slope, a is the acceleration, and δ is the rotation mass conversion factor.

[0153] The fuel cell model is constructed specifically as follows:

[0154] Fuel cells require auxiliary devices to maintain their normal operation, and these auxiliary devices will also consume part of the power generated by the stack; therefore, the output power of the fuel cell system is shown as follows:

[0155] P fcs =P stack -P aux (4)

[0156] Where P stack is the fuel cell stack output power, P aux To consume power for auxiliary devices;

[0157] The current of the fuel cell is related to the reaction rate of hydrogen and oxygen. The hydrogen consumption rate is calculated by the current:

[0158]

[0159] In the formula, is the hydrogen consumption rate, N cell is the number of fuel cell cells, is the molar mass of hydrogen, is the number of electrons in the hydrogen molecule, F is the Faraday constant, I stack is the fuel cell stack current;

[0160] Given the hydrogen consumption rate, the fuel cell system efficiency is the ratio of the fuel cell system output power to the power that can be generated when consuming hydrogen:

[0161]

[0162] Where η fcs is the fuel cell system efficiency, P fcs is the fuel cell system power, Hydrogen has a low calorific value.

[0163] The fuel cell used in this embodiment has a rated power of 30 kW and is composed of 220 fuel cell cells. According to the test data of the fuel cell system test bench, the final calculated fuel cell system hydrogen consumption rate and system efficiency curve are as follows: Figure 3 shown.

[0164] The power battery model is constructed specifically as follows:

[0165] The power battery internal resistance model is an equivalent circuit model that has been widely used in the study of energy management strategies. Ignoring the effects of temperature and aging on the power battery, the power battery internal resistance model is shown in equations (7)-(9):

[0166] U bat =U OCV -I b R b (20)

[0167]

[0168]

[0169] Where U bat is the terminal voltage of the power battery, U OCV is the open circuit voltage of the power battery, I b is the power battery current, R b is the internal resistance of the power battery, P bat is the power of the power battery;

[0170] Power BatteryU OCV and R b There is a certain correlation with the state of charge SOC; the SOC is calculated using the ampere-hour integration method, which is expressed as follows:

[0171]

[0172] Among them, Q max is the maximum capacity of the power battery, and Δt is the step length.

[0173] Figure 4 The single cell U used is given OCV and R b As the SOC changes, the internal resistance is relatively high when the SOC is at a low value, which leads to a decrease in the efficiency of the power battery; and when the SOC is at a high value, the internal resistance also begins to rise. Therefore, the SOC is controlled at 40%-60%.

[0174] The driving motor model is constructed specifically as follows:

[0175] The main function of the drive motor is to convert the electrical energy output by the power source into mechanical energy to drive the vehicle. This conversion involves the working efficiency of the motor. Figure 5 As shown, a static efficiency map is established, and a drive motor model is built based on the static efficiency map: the working efficiency of the drive motor is a function of the current torque and speed, and the relationship is as follows:

[0176] η mot =f m (T mot ,n mot ) (twenty four)

[0177] Where η mot is the motor efficiency, T mot is the motor torque, n mot is the motor speed, f m (·) is the corresponding efficiency lookup function.

[0178] S2: Based on the fuel cell hybrid system model built in S1, analyze the voltage hysteresis of the fuel cell;

[0179] S201: Analyze the voltage characteristics of the fuel cell and measure the ohmic internal resistance value;

[0180] Current research usually assumes that the fuel cell system can run in real time at the optimal output power point calculated by the energy management strategy. However, the actual situation is that due to the voltage hysteresis of the fuel cell, its output power cannot reach the optimal power output point immediately, but needs a certain lag time to reach it, thus affecting the economy of the hybrid system. Therefore, it is necessary to analyze the voltage hysteresis of the fuel cell.

[0181] The fuel cell voltage is expressed as follows:

[0182] U cell =E nernst -U act -U ohm -U con (12)

[0183] U stack =N cell U cell (13)

[0184] Where U cell is the single cell voltage, E nernst is the Nernst voltage, U act is the activation loss voltage, U ohm is the ohmic loss voltage, U con is the concentration loss voltage, U stack is the stack voltage, N cell is the number of single battery cells;

[0185] The fuel cell stack output power can be calculated using the following formula:

[0186] P stack =U stack I stack (14)

[0187] Where P stack is the fuel cell stack output power, I stack is the stack current;

[0188] When the load current changes transiently, the voltage of the fuel cell is flexible and does not change immediately. It first undergoes a sudden change and then slowly reaches a stable value. After analysis, the sudden change of voltage is mainly caused by the ohmic loss voltage. The ohmic loss voltage satisfies Ohm's law, as shown in formula (15):

[0189] U ohm =I stack R ohm (15)

[0190] In the formula, R ohm is the ohmic internal resistance;

[0191] This embodiment uses the current interruption method to measure the ohmic internal resistance. The basic principle is to make the fuel cell operate stably under a specific current, and then instantly cut off the load current. At this time, the ohmic internal resistance will change rapidly with the change of the working current, and there will be no hysteresis effect. In actual application, the current step method is usually used to test the ohmic internal resistance. The specific working principle is as follows Figure 6 As shown, the working current of the fuel cell is stepped by the electronic load, the fuel cell current step point is set, and the corresponding voltage change is recorded; then, the voltage fast change part ΔU is calculated by formula (16): ohm The ratio between the current step value ΔI and the ohmic internal resistance R is obtained. ohm ;

[0192]

[0193] In order to measure the ohmic internal resistance of the fuel cell, a total of 10 fuel cell current step points are set, as shown in Table 2. Figure 7 (a) is the overall operation data of the stack output current and output voltage. At each current step point, wait for a period of time for the system to reach a stable state, record the corresponding voltage output value, and finally plot the measured data points into a polarization characteristic curve, such as Figure 7 (b). Figure 7 (b) It can be seen that when the current is in the range of 0-30A, the voltage drops rapidly as the current increases, indicating that it is in the activation polarization region; and when the current is in the range of 30-200A, the voltage decreases approximately linearly as the current increases, indicating that it is in the ohmic polarization region. Therefore, during the entire test process, the main focus was on the ohmic polarization region, and the ohmic polarization impedance has always played a dominant role, while the activation and concentration polarization impedances accounted for a relatively low proportion and had a relatively small impact.

[0194] Table 2 Output current-voltage-power of fuel cell stack

[0195]

[0196] Figure 8 is the ohmic internal resistance at each current step point calculated based on bench test data. Figure 8It can be seen that the ohmic internal resistance ranges from 0.213Ω to 0.399Ω. When the output current of the fuel cell is small, the ohmic internal resistance is large; conversely, when the current is large, the ohmic internal resistance is small. In addition, as the current increases, the ohmic internal resistance begins to gradually decrease, and tends to stabilize after the current reaches a certain value. According to the analysis of the reaction process mechanism of the fuel cell, in the initial stage, that is, when the current is small, the fuel cell membrane is relatively dry, and the water generated by the stack cannot keep the membrane fully humidified. The water content in the membrane gradually decreases, resulting in slow material transfer, which leads to a large ohmic internal resistance. However, as the output current increases, the internal moisture generation rate accelerates, which increases the moisture content in the proton exchange membrane and the catalyst layer, accelerates the transmission rate, and thus reduces the ohmic internal resistance.

[0197] S202: based on the result of S201, obtaining the output voltage and actual output power of the fuel cell after the current changes load, specifically including fitting the hysteresis voltage process of the fuel cell, obtaining the time constant τ according to the fitting result, and obtaining the load addition and subtraction hysteresis equation according to the fitting result and the time constant, so as to obtain the output voltage and actual output power of the fuel cell after the current changes load;

[0198] Based on the results of S201, when the external current changes transiently, the voltage of the fuel cell will produce a transient value ΔU ohm , then the voltage will slowly tend to a stable state, such as Figure 6 This gentle voltage change process conforms to the change trend of the zero-state response curve of the first-order RC circuit, as shown in Fig. 9 Therefore, the zero-state response equation of the first-order RC circuit is used to fit this gentle voltage change process, as shown in equation (17):

[0199] U c (t) = U s (1-e -t / t ) (17)

[0200] Where U c (t) is the voltage across the capacitor at time t, U s is the stable value of the voltage across the capacitor, t represents time, and τ is the time constant;

[0201] Based on formula (17) and combined Fig. 9 And the actual change of fuel cell voltage, we can get:

[0202] △U del =U stea -(U k-1 -△U ohm ) (18)

[0203] U t (t)=△U del (1-e-t / t ) (19)

[0204] In the formula, ΔU del is the hysteresis voltage of the fuel cell when the current changes with the load, U stea is the stable voltage after the current changes load, U k-1 is the stable voltage before the current changes load, ΔU ohm The voltage rapid change part caused by the ohmic internal resistance, U t (t) is the output voltage at time t after the current load changes;

[0205] according to Figure 7 (a) The collected voltage data is fitted according to formula (19) for the gentle voltage change process at the six current step points. Table 3 lists the time constant τ values ​​corresponding to the minimum voltage fitting error, that is, the best fitting results. It can be seen from Table 3 that under different current loads, the time constant τ ranges from 43.86s to 55.68s. Although the time required for the battery stack voltage to reach a stable state varies slightly under different current loads, the overall change in the time constant is not significant. Therefore, in this embodiment, the time constant value is set to the mean τ avg =50s.

[0206] Table 3 Time constants at different current step points

[0207] serial number Current step point (A) Time constant τ(s) 1 30-60 53.29 2 60-80 43.86 3 80-100 45.38 4 120-140 55.68 5 160-180 47.75 6 180-200 52.07

[0208] Fig.10 (af) presents the results of voltage data obtained by the best fitting method and the average fitting method. It can be seen from the figure that the difference between the voltage curves obtained by the best fitting method and the average fitting method is small, and both τ values ​​can fit the voltage changes well. Therefore, the time constant can be set to the average value, that is, τ avg =50s.

[0209] Fig.10 (af) presents the steady process of voltage change during current loading. When the fuel cell load current decreases, its response speed is significantly faster than when the load increases. This shows that if the time constant during current unloading is set to the same value as that during current loading, it will not exceed the dynamic response capability of the fuel cell. Therefore, this embodiment chooses to use the same time constant during loading and unloading. This approach aims to simplify the model while ensuring the accuracy of the analysis and fully considering the dynamic response capability of the fuel cell. Based on the above analysis, combined with the actual change trend of the fuel cell voltage during load reduction and the zero-state response equation of the first-order RC circuit, the voltage fitting equation during load reduction can be obtained as:

[0210] U t (t)=△Udel e -t / t (20)

[0211] Therefore, by using equations (19) and (20) and combining the voltage at the previous moment, the output voltage that the fuel cell system can reach after the load current jumps t seconds later is calculated; by multiplying it with the current value after the step, the actual output power of the fuel cell system can be obtained, which is:

[0212] P load,act =U t (t)I (21)

[0213] Where I is the current after the step.

[0214] S3: Based on the results of S1 and S2, an energy management strategy considering the voltage hysteresis of the fuel cell is proposed;

[0215] S301: Ensure that the hybrid power system meets the power required by the load through the control principle of the equivalent hydrogen consumption minimum strategy, and quantitatively analyze the impact of the fuel cell voltage hysteresis on power distribution;

[0216] The core idea of ​​the equivalent hydrogen consumption minimum strategy ECMS is to convert the electric energy consumption of the power battery into equivalent hydrogen consumption, and to achieve energy distribution with the goal of minimizing the total equivalent hydrogen consumption. In the equivalent hydrogen consumption minimum strategy, the state variable is set to the power battery SOC, and the control variable of the optimization problem is set to the output power P of the fuel cell. fcs ; Therefore, the energy distribution problem of the fuel cell hybrid system can be transformed into:

[0217] minC total =min(C fcs +κC bat ) (twenty two)

[0218] In the formula, C total is the total equivalent hydrogen consumption, C fcs is the direct hydrogen consumption of the fuel cell system, C bat is the indirect equivalent hydrogen consumption of the power battery, κ is the compensation coefficient related to the power battery SOC; where C fcs =cP fcs , c is obtained by fitting the fuel cell bench experimental data;

[0219] In normal operation, the energy source of a fuel cell hybrid vehicle is the fuel cell system; therefore, when evaluating the economic performance of the vehicle, it is necessary to convert the power consumed by the power battery into equivalent hydrogen consumption. The equivalent hydrogen consumption C bat The calculation is as follows:

[0220]

[0221] Where P bat is the power battery output power, C fc,avg is the average hydrogen consumption of the fuel cell, η chg,avg is the average charging efficiency of the power battery, P fc,avg is the average power of the fuel cell, η dis is the power battery discharge efficiency, η chg is the power battery charging efficiency, η dis,avg is the average discharge efficiency of the power battery;

[0222] During the operation of the power battery, the calculation formulas for the real-time charging efficiency and the real-time discharging efficiency are as follows:

[0223]

[0224] In the formula, R dis is the internal resistance of the power battery during discharge, R chg is the internal resistance of the power battery when charging, U OCV is the open circuit voltage of the power battery;

[0225] In order to ensure that the power battery SOC works within a reasonable range and prevent the power battery from being overcharged or over-discharged, it is necessary to introduce a compensation coefficient κ related to the power battery SOC; the compensation coefficient κ is expressed as:

[0226]

[0227] In the formula, μ is the balance coefficient, SOC L is the lower limit of the power battery SOC, SOC H The upper limit of the power battery SOC;

[0228] In order to ensure that the hybrid system can meet the power required by the load and ensure the normal operation of the entire system, the following constraints need to be considered when solving the optimization problem:

[0229]

[0230] Where P load is the load power demand, P fcs is the fuel cell system power, P bat is the power of the power battery, P bat,min is the minimum output power of the power battery, P bat,max is the maximum output power of the power battery, P fcs,max is the maximum output power of the fuel cell system, △P fcs,min is the minimum power variation range of the fuel cell system, △P fcs,max is the maximum power variation range of the fuel cell system;

[0231] pass Figure 7 (a) It can be observed that when the load current changes transiently, the current can quickly approach the set expected value, but the corresponding voltage changes slowly and cannot respond as quickly as expected. According to Table 3, this delay is about 50s. In order to quantitatively analyze the impact of fuel cell voltage hysteresis on power distribution, Figure 7 The current step point is selected in (a) to analyze the difference between the actual output power of the fuel cell and the expected output power, so as to calculate the power hysteresis rate. The power hysteresis rate is calculated as follows:

[0232]

[0233] Where L is the power hysteresis rate, P tar is the fuel cell power at the target current load when stable, P inst is the output power that the fuel cell can achieve after the current step occurs t seconds, ΔP L It is the difference between the fuel cell power when it is stable under the target current load and the fuel cell power when it is stable under the starting current load.

[0234] Table 4 shows the power hysteresis rate at different current step points. In addition to the commonly used 1s energy distribution calculation step, Table 4 also shows the power hysteresis rate at 5s. It can be seen from Table 4 that at 1s, when the load current is low, that is, 30-60A, the power hysteresis rate of the fuel cell is only 2.08%, showing a small hysteresis phenomenon. However, with the increase of load current, the power hysteresis rate generally shows an increasing trend, up to 15.73%. At 5s, there is also a large hysteresis rate at each current step point, up to 7.68%. This also intuitively shows that the fuel cell cannot reach the optimal power output point in an instant. This time is usually greater than the calculation step of 1s for energy distribution, and its voltage hysteresis will have a greater impact on the distribution of energy management. When the output power of the fuel cell cannot meet the load demand, the system needs to rely on the power battery to provide additional power support to meet the power demand. This will cause the dual power source to deviate from the optimal power output point, thereby increasing the hydrogen consumption of the hybrid system.

[0235] Table 4 Power hysteresis rate at different current step points

[0236]

[0237] S302: Based on the control principle of the equivalent hydrogen consumption minimum strategy in S301, an energy management strategy considering the voltage hysteresis of the fuel cell is proposed;

[0238] Based on the S301 equivalent hydrogen consumption minimum strategy, that is, the above formulas (22-26), the fuel cell voltage hysteresis equation, that is, the above formula (20), is proposed to accurately describe the voltage hysteresis phenomenon of the fuel cell, so as to dynamically adjust the constraint condition of the cost function, that is, the above formula (26), to optimize the output power of the fuel cell; Fig.11 As shown in the figure, the improved equivalent hydrogen consumption minimum strategy solution process is as follows:

[0239] According to the vehicle speed V at time k act (k) and acceleration a act (k), the load demand power P at time k is calculated by the above formula (3) load,act (k):

[0240]

[0241] According to the equivalent hydrogen consumption minimum strategy, that is, the above formula (22-26), according to the actual load power demand P load,act (k) Perform energy distribution and calculate the expected power P of the fuel cell system at time k fcs,tar (k) specifically:

[0242] minC total =min(C fcs +κC bat )

[0243] C fcs =cP fcs,tar (k)

[0244]

[0245] P load,act (k) = P fcs,tar(k) +P bat

[0246] Combined with the voltage hysteresis equation, that is, the above formula (20), the fuel cell cost function is updated to solve the constraint condition, that is, the fuel cell output power range in the above formula (26), which is 0 to the maximum output power P of the fuel cell system when loaded fcs,max , when the load is reduced, it is 0 to the minimum output power P of the fuel cell system fcs,min , as follows:

[0247] U t (t)=△U del e -t / t

[0248]

[0249] According to the actual load power required at time k, P load,act(k) Energy distribution, that is, the above formula (22-26), solves the optimal power P that the fuel cell can achieve at time k fcs,act (k) specifically:

[0250] minC total =min(C fcs +κC bat )

[0251] C fcs =cP fcs,act (k)

[0252]

[0253] P load,act (k) = P fcs,act(k) +P bat

[0254] S303: Verify the effectiveness of the energy management strategy considering the voltage hysteresis of the fuel cell;

[0255] Since the characteristic parameters of different working conditions are different, the change of load demand power will also be different under each corresponding working condition. In order to fully verify the effectiveness of the fuel cell energy management strategy proposed in this paper, simulation analysis will be carried out through four real vehicle operating conditions, namely high speed, medium speed, low speed and comprehensive conditions, such as Fig.12 (ad) shown.

[0256] Fig.13 (ad) is the comparison of simulation results before and after the improvement of energy management strategy under high-speed conditions. When the load demand power change is small, such as Fig.13Near the 1000th vehicle speed point in (ac), the fuel cell output power calculated by the energy management strategy also changes little, and the voltage hysteresis of the fuel cell has little effect on the output power. At this time, the fuel cell power calculated by the traditional ECMS and the improved ECMS in the fuel cell model considering voltage hysteresis is basically the same. However, when the load demand power changes greatly, as shown in the enlarged diagrams (I) and (II), the static expected power of the fuel cell changes rapidly with the load demand power within the constraint range, which will cause the power change rate of the fuel cell to be large, further increasing the influence of the voltage hysteresis of the fuel cell. This means that the fuel cell can only output according to the current maximum power, causing the actual output power to deviate from the static expected power point of the fuel cell. To solve this problem, the improved ECMS considers the voltage hysteresis of the fuel cell while updating the dynamic output power of the fuel cell to the constraint conditions in real time. In this way, the local optimal power can be solved within the power range that the fuel cell can output. Specifically, as reflected in the figure, the dynamic output power curve of the fuel cell cannot completely follow the static expected power curve of the fuel cell. Therefore, the fuel cell outputs according to the power curve allocated by the improved ECMS strategy. However, it is worth noting that at certain vehicle speed points, the dynamic output power curve partially overlaps with the optimized fuel cell power curve, which means that at these vehicle speed points, the local optimal power remains unchanged.

[0257] Depend on Fig.13 (d) It can be seen that the improved ECMS can effectively control the fluctuation range of the power battery SOC and maintain the SOC at around 60%. In addition, compared with the ECMS before improvement, the SOC fluctuation range in the improved ECMS is increased. This is because under certain high-power load requirements, there is voltage lag in the fuel cell, which causes the power battery to bear more power distribution. However, after a period of adjustment and recovery, the SOC will gradually return to near the preset reference value. This shows that the improved ECMS has a good energy management effect and can achieve stable and reliable SOC control during the charging and discharging process of the power battery.

[0258] Fig.14 (ad) is the comparison of simulation results before and after the improved energy management strategy under medium speed conditions. Fig.14It can be seen that the trend of fuel cell output power change under medium-speed conditions is similar to that under high-speed conditions. When the load demand power changes slightly, the performance difference between the improved ECMS and the traditional ECMS is not significant. However, when the load demand power changes greatly, the improved ECMS shows its advantages in power distribution control and can achieve local optimal power output within the current output power range of the fuel cell. In addition, the simulation results under the two conditions are mainly reflected in the changes in SOC. Moreover, because the vehicle accelerates and decelerates more frequently under medium-speed conditions, the load demand power fluctuates more frequently. Therefore, under medium-speed conditions, the fluctuation frequency of SOC is higher than that of high-speed conditions, but the fluctuation range is relatively small.

[0259] Fig.15 (ab) is a comparison of simulation results before and after the improved energy management strategy under low-speed conditions. As can be seen from the figure, compared with high-speed and medium-speed conditions, the load demand power under low-speed conditions is generally smaller, and the rate of change of load power is also relatively small. Therefore, from the perspective of the entire test results, the fuel cell output power curves calculated by the two energy management strategies are basically the same. Only when some load demand power changes greatly, the improved ECMS will play its advantages and ensure more precise power control. In addition, it can be observed from the SOC curve that under low-speed conditions, the SOC fluctuates within a very small range.

[0260] Fig.16 (ad) is a comparison of simulation results before and after the improved energy management strategy under comprehensive working conditions. It can be observed that the output power law of the fuel cell under comprehensive working conditions is consistent with the law under high-speed, medium-speed and low-speed working conditions considered separately before. This shows that whether it is under high-speed, medium-speed or low-speed working conditions, the working state and energy management strategy of the fuel cell are basically consistent, and respond appropriately to the load demand. In addition, under comprehensive working conditions, the change trend of SOC is consistent with the trend in the previous individual working conditions, and the SOC values ​​before and after optimization are close. This means that the proposed energy management strategy can effectively control the change of SOC and maintain a reasonable charging and discharging range of the power battery under different working conditions.

[0261] The equivalent hydrogen consumption of the two energy management strategies under various working conditions is shown in Table 5. It can be seen from Table 5 that the economy of the improved ECMS under four different working conditions has been improved. Specifically, it has been improved by 1.58% under high-speed conditions, 3.55% under medium-speed conditions, 0.29% under low-speed conditions, and 2.02% under comprehensive conditions. Among them, the economy of medium-speed conditions has been improved most significantly. This result shows that under medium-speed conditions, the vehicle speed changes more frequently, resulting in more moments of load demand power changes. These moments will cause the fuel cell demand power calculated by the ECMS that does not consider the influence of fuel cell hysteresis to deviate from the actual output power, so its economy is poor. On the other hand, under low-speed conditions, due to the small change in vehicle speed and relatively stable working conditions, the economic differences between the two ECMS are not large. This shows that only when the load demand power changes greatly, the improved ECMS considering the hysteresis of fuel cell voltage can show better economy.

[0262] Table 5 Comparative analysis of economic performance under various working conditions

[0263]

[0264] The present invention can achieve local optimal output power within the power range that the fuel cell can output, effectively reduce the impact of the voltage hysteresis of the fuel cell, and effectively improve the economy. First, the voltage hysteresis of the fuel cell was studied through the fuel cell bench test data, and the ohmic internal resistance value and the average time constant of the zero-state response under different load currents were analyzed respectively. Subsequently, based on the existing fuel cell static efficiency model, the voltage hysteresis equation was introduced into the equivalent hydrogen consumption minimum strategy, which accurately characterized the hysteresis power of the fuel cell when the load changes, updated the constraints of the cost function in real time, and proposed an equivalent hydrogen consumption minimum strategy considering the voltage hysteresis of the fuel cell. Finally, the effectiveness of the proposed strategy was verified under four working conditions.

[0265] A device for a hybrid system energy management method considering battery hysteresis includes a data acquisition module, a model building module, a control optimization module, and an energy management module.

[0266] The data acquisition module is used to extract the main relevant parameters of the whole vehicle, the relevant parameters of the fuel cell, the relevant parameters of the power battery, the relevant parameters of the drive motor, the speed and acceleration parameters;

[0267] The model building module is used to establish a fuel cell model by using the relationship between the hydrogen consumption rate and the efficiency of the fuel cell system; to establish a power battery model by using the relationship between parameters such as the battery open circuit voltage and internal resistance; and to establish a drive motor model by using a static efficiency MAP diagram;

[0268] The control optimization module is used to calculate the required load power based on the data in the data acquisition module, and then distribute the energy according to the equivalent hydrogen consumption minimum strategy to calculate the expected power of the fuel cell; based on the calculated expected power of the fuel cell, considering the hysteresis of the fuel cell, a fuel cell voltage hysteresis equation is proposed, so as to dynamically adjust the constraint conditions of the cost function to optimize the output power of the fuel cell;

[0269] The energy management module is used to distribute energy based on the optimized fuel cell output power and the required load power according to the equivalent hydrogen consumption minimum strategy, and calculate the optimal power that the fuel cell can achieve.

[0270] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0271] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A hybrid system energy management method considering battery hysteresis, characterized in that: The following steps are involved: S1: Construction of fuel cell hybrid system model, including powertrain system construction, fuel cell model construction, power battery model construction, and drive motor model construction; S2: Based on the fuel cell hybrid system model built in S1, analyze the voltage hysteresis of the fuel cell; S201: Analyze the voltage characteristics of the fuel cell and measure the ohmic internal resistance value; S202: based on the result of S201, obtaining the output voltage and actual output power of the fuel cell after the current changes load, specifically including fitting the hysteresis voltage process of the fuel cell, obtaining the time constant τ according to the fitting result, and obtaining the load addition and subtraction hysteresis equation according to the fitting result and the time constant, so as to obtain the output voltage and actual output power of the fuel cell after the current changes load; S3: Based on the results of S1 and S2, an energy management strategy considering the voltage hysteresis of the fuel cell is proposed; S301: Ensure that the hybrid power system meets the power required by the load through the control principle of the equivalent hydrogen consumption minimum strategy, and quantitatively analyze the impact of the fuel cell voltage hysteresis on power distribution; S302: Based on the control principle of the equivalent hydrogen consumption minimum strategy in S301, an energy management strategy considering the voltage hysteresis of the fuel cell is proposed; S303: Verify the effectiveness of the energy management strategy considering the fuel cell voltage hysteresis.

2. The hybrid system energy management method considering battery hysteresis according to claim 1, characterized in that: The powertrain system is specifically constructed as follows: Choose to build a hybrid system by connecting fuel cells and power batteries in parallel. The fuel cells mainly provide the power required for the vehicle to travel smoothly, while the power batteries are used to alleviate power peaks and valleys. During driving, the driving resistance includes the wheel rolling resistance F f , slope resistance F i , air resistance F w , acceleration resistance F a , the calculation formulas of each resistance are as follows: According to the force balance relationship, the driving force F of the vehicle t The calculation formula is as follows: F t =F f +F i +F w +F a (2) The required power of DC bus P load It can be derived from the vehicle longitudinal dynamics model, and the calculation formula is as follows: In the formula, F t is the driving force, η t is the transmission system efficiency, η m is the motor efficiency, v is the vehicle speed, m is the total mass, f is the rolling coefficient, Cd is the air resistance coefficient, A is the frontal area, g is the acceleration of gravity, α is the angle corresponding to the road slope, a is the acceleration, and δ is the rotation mass conversion factor.

3. The hybrid system energy management method considering battery hysteresis according to claim 2, characterized in that: The fuel cell model is constructed specifically as follows: Fuel cells require auxiliary devices to maintain their normal operation, and these auxiliary devices will also consume part of the power generated by the stack; therefore, the output power of the fuel cell system is shown as follows: P fcs =P stack -P aux (4) Where P stack is the fuel cell stack output power, P aux To consume power for auxiliary devices; The current of the fuel cell is related to the reaction rate of hydrogen and oxygen. The hydrogen consumption rate is calculated by the current: In the formula, is the hydrogen consumption rate, N cell is the number of fuel cell cells, is the molar mass of hydrogen, is the number of electrons in the hydrogen molecule, F is the Faraday constant, I stack is the fuel cell stack current; Given the hydrogen consumption rate, the fuel cell system efficiency is the ratio of the fuel cell system output power to the power that can be generated when consuming hydrogen: Where η fcs is the fuel cell system efficiency, P fcs is the fuel cell system power, Hydrogen has a low calorific value.

4. The hybrid system energy management method considering battery hysteresis according to claim 3, characterized in that: The power battery model is constructed specifically as follows: Ignoring the effects of temperature and aging on the power battery, the internal resistance model of the power battery is shown in equations (7)-(9): U bat =U OCV -I b R b (4) Where U bat is the terminal voltage of the power battery, U OCV is the open circuit voltage of the power battery, I b is the power battery current, R b is the internal resistance of the power battery, P bat is the power of the power battery; Power BatteryU OCV and R b There is a certain correlation with the state of charge SOC; the SOC is calculated using the ampere-hour integration method, which is expressed as follows: Among them, Q max is the maximum capacity of the power battery, and Δt is the step length.

5. The hybrid system energy management method considering battery hysteresis according to claim 4, characterized in that: The driving motor model is constructed as follows: Establish a static efficiency map, and build a drive motor model based on the static efficiency map: The working efficiency of the drive motor is a function of the current torque and speed, and the relationship is as follows: or mot =f m (T mot ,n mot ) (8) Where η mot is the motor efficiency, T mot is the motor torque, n mot is the motor speed, f m (·) is the corresponding efficiency lookup function.

6. The hybrid system energy management method considering battery hysteresis according to claim 5, characterized in that: The S201 is specifically as follows: The fuel cell voltage is expressed as follows: IN cell =E nernst -IN act -IN ohm -IN con (12) U stack =N cell U cell (13) Where U cell is the single cell voltage, E nernst is the Nernst voltage, U act is the activation loss voltage, U ohm is the ohmic loss voltage, U con is the concentration loss voltage, U stack is the stack voltage, N cell is the number of single battery cells; The fuel cell stack output power can be calculated using the following formula: P stack =U stack AND stack (14) Where P stack is the fuel cell stack output power, I stack is the stack current; When the load current changes transiently, the voltage of the fuel cell is flexible and does not change immediately. It first undergoes a sudden change and then slowly reaches a stable value. After analysis, the sudden change of voltage is mainly caused by the ohmic loss voltage. The ohmic loss voltage satisfies Ohm's law, as shown in formula (15): U ohm =I stack R ohm (15) In the formula, R ohm is the ohmic internal resistance; The working current of the fuel cell is made to step by the electronic load, the fuel cell current step point is set, and the corresponding voltage change is recorded; Then, the voltage rapid change part ΔU is calculated by equation (16): ohm The ratio between the current step value ΔI and the ohmic internal resistance R is obtained. ohm。 7. The hybrid system energy management method considering battery hysteresis according to claim 6, characterized in that: The S202 is specifically as follows: Based on the results of S201, when the external current changes transiently, the voltage of the fuel cell will produce a transient value ΔU ohm , then the voltage will slowly tend to a stable state. This gentle voltage change process is consistent with the change trend of the zero-state response curve of the first-order RC circuit. Therefore, the zero-state response equation of the first-order RC circuit is used to fit this gentle voltage change process, as shown in formula (17): U c (t)=U s (1-e -t / t ) (17) Where U c (t) is the voltage across the capacitor at time t, U s is the stable value of the voltage across the capacitor, t represents time, and τ is the time constant; Based on equation (17) and the actual change of the fuel cell voltage, it can be obtained: △U del =U stea -(IN k-1 -△U ohm ) (18) U t (t)=△U del (1-e -t / t ) (19) In the formula, ΔU del is the hysteresis voltage of the fuel cell when the current changes with the load, U stea is the stable voltage after the current changes load, U k-1 is the stable voltage before the current changes load, ΔU ohm The voltage rapid change part caused by the ohmic internal resistance, U t (t) is the output voltage at time t after the current load changes; According to the voltage data obtained in S201, the gentle voltage change process at the current step point is fitted according to formula (19) to obtain the time constant τ value corresponding to the minimum voltage fitting error, that is, the best fitting result. According to the time constant τ values ​​at different current step points, the average τ is selected. avg ; According to the steady process of voltage change during current loading in S201, it is known that when the fuel cell load current decreases, its response speed is significantly faster than when the load increases. If the time constant during current reduction is set to the same value as that during current loading, it will not exceed the dynamic response capability of the fuel cell; therefore, the same time constant is selected during loading and unloading; combined with the actual change trend of the fuel cell voltage during load reduction and the zero-state response equation of the first-order RC circuit, the voltage fitting equation during load reduction is obtained as follows: U t (t)=△U del e -t / t (20) Therefore, by using equations (19) and (20) and combining the voltage at the previous moment, the output voltage that the fuel cell system can reach after the load current jumps t seconds later is calculated; by multiplying it with the current value after the step, the actual output power of the fuel cell system can be obtained, which is: P load,act =U t (t)I (21) Where I is the current after the step.

8. The hybrid system energy management method considering battery hysteresis according to claim 7, characterized in that: The S301 is specifically as follows: In the equivalent hydrogen consumption minimization strategy, the state variable is set to the power battery SOC, and the control variable of the optimization problem is set to the output power P of the fuel cell. fcs ; Therefore, the energy distribution problem of the fuel cell hybrid system can be transformed into: minC total =min(C fcs +κC bat ) (22) In the formula, C total is the total equivalent hydrogen consumption, C fcs is the direct hydrogen consumption of the fuel cell system, C bat is the indirect equivalent hydrogen consumption of the power battery, κ is the compensation coefficient related to the power battery SOC; where C fcs =cP fcs , c is obtained by fitting the fuel cell bench experimental data; In normal operation, the energy source of a fuel cell hybrid vehicle is the fuel cell system; therefore, when evaluating the economic performance of the vehicle, it is necessary to convert the power consumed by the power battery into equivalent hydrogen consumption. The equivalent hydrogen consumption C bat The calculation is as follows: Where P bat is the power battery output power, C fc,avg is the average hydrogen consumption of the fuel cell, η chg,avg is the average charging efficiency of the power battery, P fc,avg is the average power of the fuel cell, η dis is the power battery discharge efficiency, η chg is the power battery charging efficiency, η dis,avg is the average discharge efficiency of the power battery; During the operation of the power battery, the calculation formulas for the real-time charging efficiency and the real-time discharging efficiency are as follows: In the formula, R dis is the internal resistance of the power battery during discharge, R chg is the internal resistance of the power battery when charging, U OCV is the open circuit voltage of the power battery; In order to ensure that the power battery SOC works within a reasonable range and prevent the power battery from being overcharged or over-discharged, it is necessary to introduce a compensation coefficient κ related to the power battery SOC; the compensation coefficient κ is expressed as: In the formula, μ is the balance coefficient, SOC L is the lower limit of the power battery SOC, SOC H The upper limit of the power battery SOC; In order to ensure that the hybrid system can meet the power required by the load and ensure the normal operation of the entire system, the following constraints need to be considered when solving the optimization problem: Where P load is the load power demand, P fcs is the fuel cell system power, P bat is the power of the power battery, P bat,min is the minimum output power of the power battery, P bat,max is the maximum output power of the power battery, P fcs,max is the maximum output power of the fuel cell system, △P fcs,min is the minimum power variation range of the fuel cell system, △P fcs,max is the maximum power variation range of the fuel cell system; In order to quantitatively analyze the influence of fuel cell voltage hysteresis on power distribution, n current step points are selected to analyze the difference between the actual output power and the expected output power of the fuel cell, so as to calculate the power hysteresis rate; the power hysteresis rate is calculated as follows: Where L is the power hysteresis rate, P tar is the fuel cell power at the target current load when stable, P inst is the output power that the fuel cell can achieve after the current step occurs t seconds, ΔP L It is the difference between the fuel cell power when it is stable under the target current load and the fuel cell power when it is stable under the starting current load.

9. The hybrid system energy management method considering battery hysteresis according to claim 8, characterized in that: The S302 is specifically as follows: Based on the S301 equivalent hydrogen consumption minimum strategy, that is, the above formula (22-26), the fuel cell voltage hysteresis equation, that is, the above formula (20), is proposed to accurately describe the voltage hysteresis phenomenon of the fuel cell, so as to dynamically adjust the constraint condition of the cost function, that is, the above formula (26), to optimize the output power of the fuel cell; the specific solution process of the improved equivalent hydrogen consumption minimum strategy is: According to the vehicle speed V at time k act (k) and acceleration a act (k), the load demand power P at time k is calculated by the above formula (3) load,act (k): According to the equivalent hydrogen consumption minimum strategy, that is, the above formula (22-26), according to the actual load power demand P load,act (k) Perform energy distribution and calculate the expected power P of the fuel cell system at time k fcs,tar (k) specifically: minC total =min(C fcs +κC bat ) C fcs cP fcs,tar (k) P load,act (k)=P fcs,tar(k) +P bat Combined with the voltage hysteresis equation, that is, the above formula (20), the fuel cell cost function is updated to solve the constraint condition, that is, the fuel cell output power range in the above formula (26), which is 0 to the maximum output power P of the fuel cell system when loaded fcs,max , when the load is reduced, it is 0 to the minimum output power P of the fuel cell system fcs,min , as follows: U t (t)=△U del e -t / t According to the actual load power required at time k, P load,act (k) Energy distribution, that is, the above formula (22-26), solves the optimal power P that the fuel cell can achieve at time k fcs,act (k) specifically: minC total =min(C fcs +κC bat ) C fcs cP fcs,act (k) P load,act (k)=P fcs,act(k) +P bat。 10. A device for implementing the hybrid system energy management method considering battery hysteresis as claimed in claim 9, characterized in that: Including data acquisition module, model building module, control optimization module, energy management module, The data acquisition module is used to extract the main relevant parameters of the whole vehicle, the relevant parameters of the fuel cell, the relevant parameters of the power battery, the relevant parameters of the drive motor, the speed and acceleration parameters; The model building module is used to establish a fuel cell model by using the relationship between the hydrogen consumption rate and the efficiency of the fuel cell system; to establish a power battery model by using the relationship between parameters such as the battery open circuit voltage and internal resistance; and to establish a drive motor model by using a static efficiency MAP diagram; The control optimization module is used to calculate the required load power based on the data in the data acquisition module, and then distribute the energy according to the equivalent hydrogen consumption minimum strategy to calculate the expected power of the fuel cell; based on the calculated expected power of the fuel cell, considering the hysteresis of the fuel cell, a fuel cell voltage hysteresis equation is proposed, so as to dynamically adjust the constraint conditions of the cost function to optimize the output power of the fuel cell; The energy management module is used to distribute energy based on the optimized fuel cell output power and the required load power according to the equivalent hydrogen consumption minimum strategy, and calculate the optimal power that the fuel cell can achieve.

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