Fuel cell commercial vehicle power optimization method and system based on super capacitor

Abstract

The invention relates to the technical field of power supply and distribution systems, and provides a fuel cell commercial vehicle power optimization method and system.The fuel cell commercial vehicle power optimization method comprises the following steps that a fuel cell and a power cell are combined to supply power to a load motor, and the power of the load motor is optimized according to the SOC state of the power cell; adjusting the power output of the fuel cell in different SOC states; and the SOC fluctuation state of the power battery is predicted, and the energy exchange between the power battery and the super capacitor is adjusted with the goal of minimizing the output power fluctuation frequency of the fuel battery. According to the method, the SOC fluctuation state of the power battery is predicted, energy exchange between the power battery and the super capacitor is adjusted in good time, power distribution is optimized with the goal of minimizing the output power fluctuation frequency of the fuel battery, and instability of power output of the fuel battery caused by fluctuation of the SOC near a critical value can be avoided; therefore, frequent power change of the fuel cell is reduced, and the service life is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply and distribution systems, and more particularly, to a power optimization method and system for a fuel cell commercial vehicle based on a super capacitor. Background Art

[0002] Currently, the power system of a fuel cell commercial vehicle usually adopts a combination of a fuel cell and a power battery, and the system power distribution is based on the SOC control strategy. The power output of the fuel cell is usually divided into three power ranges: large, medium, and small, and the SOC value is used as the switching standard.

[0003] The SOC control strategy can reduce the power fluctuation of the fuel cell to a certain extent. However, in the driving condition, when the SOC value is close to the switching standard, the power of the fuel cell may still fluctuate greatly. Especially in the case of frequent switching between two or more power ranges, this fluctuation will affect the output stability of the fuel cell and may shorten its service life. Summary of the Invention

[0004] To solve the problems in the prior art, the present invention provides a power optimization method and system for a fuel cell commercial vehicle based on a super capacitor. The specific technical solutions are as follows:

[0005] A power optimization method for a fuel cell commercial vehicle based on a super capacitor includes the following steps:

[0006] Combining the fuel cell and the power battery to supply power to the load motor, and adjusting the power output of the fuel cell under different SOC states according to the SOC state of the power battery;

[0007] Predicting the SOC fluctuation state of the power battery, and adjusting the energy exchange between the power battery and the super capacitor with the goal of minimizing the number of fluctuations in the fuel cell output power.

[0008] The power optimization method for the fuel cell commercial vehicle adjusts the energy exchange between the power battery and the super capacitor in a timely manner by predicting the SOC fluctuation state of the power battery. It optimizes the power distribution with the goal of minimizing the number of fluctuations in the fuel cell output power, and can avoid the instability of the fuel cell power output caused by the fluctuation of the SOC near the critical value, thereby reducing the frequent power change of the fuel cell and prolonging its service life.

[0009] Preferably, predicting the SOC fluctuation state of the power battery includes the following steps:

[0010] Obtaining the budget working state of the load motor and the budget working condition of the current road;

[0011] Predict the SOC fluctuation state of the power battery according to the budget working state and budget working condition.

[0012] Preferably, adjusting the energy exchange between the power battery and the super capacitor includes the following steps:

[0013] According to the SOC fluctuation state of the power battery, predict whether the power of the power battery is higher than the first critical value. If so, judge whether the power of the super capacitor is greater than the critical difference of the power battery. If so, charge the super capacitor through the power battery;

[0014] According to the SOC fluctuation state of the power battery, predict whether the power of the power battery is lower than the second critical value. If so, judge whether the power of the super capacitor is greater than the critical difference of the power battery. If so, charge the power battery through the super capacitor;

[0015] Wherein, the first critical value is greater than the second critical value.

[0016] Preferably, the fuel cell commercial vehicle power optimization method further includes the following steps:

[0017] Obtain the real-time power of the super capacitor;

[0018] If the real-time power is greater than the first preset multiple of the rated capacitance of the super capacitor, charge the power battery through the super capacitor to reduce the real-time power to the standard preset multiple of the rated capacitance of the super capacitor;

[0019] If the real-time power is less than the second preset multiple of the rated capacitance of the super capacitor, charge the super capacitor through the power battery to increase the real-time power to the standard preset multiple of the rated capacitance of the super capacitor;

[0020] Wherein, the first preset multiple > standard preset multiple > second preset multiple, and both the first preset multiple and the second preset multiple are in the range of (0, 1).

[0021] Preferably, the specific method for adjusting the power output of the fuel cell under different SOC states according to the SOC state of the power battery includes the following steps:

[0022] When the SOC state of the power battery is in the first state interval, adjust the power output of the fuel cell to the first power interval;

[0023] When the SOC state of the power battery is in the second state interval, adjust the power output of the fuel cell to the second power interval;

[0024] When the SOC state of the power battery is in the third state range, adjust the power output of the fuel cell to the third power range;

[0025] Among them, the lower limit value of the first state range is greater than the upper limit value of the second state range, the lower limit value of the second state range is greater than the upper limit value of the third state range, the upper limit value of the first power range is less than the lower limit value of the second power range, and the upper limit value of the second power range is less than the lower limit value of the third power range.

[0026] Preferably, the specific method for obtaining the budget working state of the load motor and the budget working condition of the current road includes the following steps:

[0027] According to the formula P eng (t) = [α·Load(t) + β·RPM(t) + γ]·K T ·K H Obtain the budget working state of the load motor;

[0028] According to the formula Obtain the budget working condition of the current road;

[0029] Among them, Load represents the real-time load signal, RPM represents the motor speed, α and β represent the weight coefficients of the real-time load signal and the motor speed respectively, γ represents the bias constant, K T 、K H respectively represent the temperature correction coefficient and the altitude correction coefficient, m represents the total vehicle mass, g represents the acceleration due to gravity, μ represents the rolling resistance coefficient, θ represents the road gradient, v represents the vehicle speed, ρ, C d 、A respectively represent the air density, the drag coefficient and the frontal area.

[0030] Preferably, the specific method for predicting the SOC fluctuation state of the power battery according to the budget working state and the budget working condition includes the following steps:

[0031] Construct an SOC change rate equation

[0032] Through the Kalman filter Real-time correct the SOC prediction error;

[0033] Among them, Q represents the rated capacity of the power battery, η ch 、η dis respectively represent the charging efficiency and the discharging efficiency, P charge (t) represents the regenerative braking feedback power, represents the optimal estimated value of SOC at the current time t, The prior predicted value of SOC at time t based on the optimal estimate at time t-1, Kt represents the Kalman gain, SOC meas,t represents the actual measured SOC value at the current time t.

[0034] A power optimization system for a fuel cell commercial vehicle based on a supercapacitor, which is used to implement the power optimization method for the fuel cell commercial vehicle, includes:

[0035] A power adjustment module, which is used to supply power to the load motor jointly by the fuel cell and the power battery, and adjust the power output of the fuel cell under different SOC states according to the SOC state of the power battery;

[0036] An electricity exchange module, which is used to predict the SOC fluctuation state of the power battery, and adjust the energy exchange between the power battery and the supercapacitor with the goal of minimizing the number of fluctuations in the fuel cell output power.

[0037] Preferably, the electricity exchange module includes:

[0038] A prediction unit, which is used to obtain the budget working state of the load motor and the budget working condition of the current road;

[0039] An SOC acquisition unit, which is used to predict the SOC fluctuation state of the power battery according to the budget working state and the budget working condition.

[0040] Preferably, the SOC acquisition unit predicts the SOC fluctuation state of the power battery according to the SOC change rate equation and the Kalman filter to predict the SOC fluctuation state of the power battery;

[0041] wherein, Load represents the real-time load signal, RPM represents the motor speed, α and β represent the weight coefficients of the real-time load signal and the motor speed, γ represents the bias constant, K T 、K H respectively represent the temperature correction coefficient and the altitude correction coefficient, m represents the total vehicle mass, g represents the acceleration due to gravity, μ represents the rolling resistance coefficient, θ represents the road slope, v represents the vehicle speed, ρ, C d 、A respectively represent the air density, the wind resistance coefficient and the frontal area, Q represents the rated capacity of the power battery, η ch 、η dis respectively represent the charging efficiency and the discharging efficiency, P charge (t) represents the regenerative braking feedback power, represents the optimal estimated value of SOC at the current time t, the prior prediction value of SOC at time t based on the optimal estimate at time t-1, K t represents the Kalman gain, SOC meas,tRepresents the actual measured SOC value at the current moment t. Brief Description of the Drawings

[0042] The present invention can be further understood from the following description in conjunction with the drawings. The components in the drawings are not necessarily drawn to scale, but the emphasis is on showing the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0043] Figure 1 Is a schematic diagram of the overall process of the power optimization method for a fuel cell commercial vehicle in an embodiment of the present invention;

[0044] Figure 2 Is a schematic diagram of the process of a specific method for predicting the SOC fluctuation state of the power battery in an embodiment of the present invention;

[0045] Figure 3 Is a schematic diagram of the process of a specific method for obtaining the budget working state of the load motor and the budget working conditions of the current road in an embodiment of the present invention;

[0046] Figure 4 Is a schematic diagram of the process of a specific method for predicting the SOC fluctuation state of the power battery in an embodiment of the present invention;

[0047] Figure 5 Is a schematic diagram of the process of a specific method for adjusting the energy exchange method between the power battery and the super capacitor in an embodiment of the present invention;

[0048] Figure 6 Is a schematic diagram of the process of the power optimization method for a fuel cell commercial vehicle in another embodiment of the present invention;

[0049] Figure 7 Is a schematic diagram of the process of a specific method for adjusting the power output of the fuel cell under different SOC states in an embodiment of the present invention;

[0050] Figure 8 Is a schematic diagram of the overall structure of the power optimization system for a fuel cell commercial vehicle in an embodiment of the present invention;

[0051] Figure 9 Is a schematic diagram of the functional structure of the power exchange module in an embodiment of the present invention;

[0052] Figure 10 Is a schematic diagram of the structure of the power optimization system for a fuel cell commercial vehicle in another embodiment of the present invention Figure 1 ;

[0053] Figure 11 Is a schematic diagram of the structure of the power optimization system for a fuel cell commercial vehicle in another embodiment of the present invention Figure 2 . Detailed Description of the Invention

[0054] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below in conjunction with its embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not limit the protection scope of the present invention.

[0055] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration and do not represent the only implementation.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0057] In the present invention, the "first" and "second" do not represent specific quantities and orders, but are only used for name distinction.

[0058] As Figure 1 shown, an embodiment of the present invention provides a power optimization method for a fuel cell commercial vehicle based on a super capacitor, including the following steps:

[0059] S1, jointly supply power to the load motor by the fuel cell and the power battery, and adjust the power output of the fuel cell under different SOC states according to the SOC state of the power battery.

[0060] Specifically, a fuel cell is a device that directly converts the chemical energy of fuel (such as hydrogen, methanol, etc.) and an oxidant (usually oxygen) into electrical energy through an electrochemical reaction. It does not need to go through a combustion process, so the energy conversion efficiency is high, and the emissions are mainly water vapor, which is very environmentally friendly. The core component of a fuel cell is the electrolyte diaphragm, which only allows corresponding ions to pass through, so as to achieve the purpose of directly converting chemical energy into electrical energy. The power battery is a power source that provides power for tools, mostly referring to the storage batteries that provide power for electric vehicles, electric trains, electric bicycles, and golf carts, including ternary lithium batteries, lithium iron phosphate batteries, lithium cobalt oxide batteries, nickel-metal hydride batteries, etc.

[0061] In this embodiment, the power optimization method is based on the existing power system of a fuel cell vehicle, and manages and optimizes the system power distribution by adding a super capacitor. The power system of the fuel cell commercial vehicle is jointly provided by a fuel cell and a power battery. The super capacitor optimizes the power distribution between the fuel cell and the power battery by adjusting the SOC of the power battery, and reduces the power range jump of the fuel cell.

[0062] S2. Predict the SOC fluctuation state of the power battery, and adjust the energy exchange between the power battery and the super capacitor with the goal of minimizing the number of fluctuations in the output power of the fuel cell.

[0063] Preferably, as Figure 5 shown, in step S2, adjusting the energy exchange between the power battery and the super capacitor includes the following steps:

[0064] S23. According to the SOC fluctuation state of the power battery, predict whether the power of the power battery is higher than the first critical value. If so, judge whether the power of the super capacitor is greater than the critical difference of the power battery. If so, charge the super capacitor through the power battery;

[0065] S24. According to the SOC fluctuation state of the power battery, predict whether the power of the power battery is lower than the second critical value. If so, judge whether the power of the super capacitor is greater than the critical difference of the power battery. If so, charge the power battery through the super capacitor;

[0066] Among them, the first critical value is greater than the second critical value. The first critical value can be understood as a high critical value, such as 0.7 or 0.8%, and the second critical value can be understood as a low critical value, such as 0.4 or 0.3, etc.

[0067] The joint use of a high-power fuel cell, a low-power power battery and a super capacitor can be adopted. The fuel cell and the power battery provide power output according to the SOC control strategy, and the instantaneous power requirements for acceleration, starting and braking energy recovery are mainly provided by the power battery. The super capacitor is used to supplement the SOC of the power battery, that is, based on the neural network to predict the SOC fluctuation state of the power battery, and adjust the energy exchange between the power battery and the super capacitor with the goal of minimizing the number of fluctuations in the output power of the fuel cell.

[0068] Specifically, the method for minimizing the number of fluctuations in fuel cell output power includes: setting a variable time interval value ΔT2 based on the global optimum, and then calculating the difference power value according to the predicted SOC fluctuation state of the power battery and having the supercapacitor compensate the power battery to reduce the frequent adjustment of the fuel cell due to sudden load fluctuations. For example, assuming that the current moment is T0, if the power battery power is lower than the low critical value of 0.4 or lower 0.3, etc. within the future time T0+ΔT2 based on the predicted SOC fluctuation state of the power battery, the supercapacitor will compensate the power battery. The critical difference here refers to the gap between the high critical value and the low critical value, which is used to ensure the flexibility of power regulation and avoid too frequent charging and discharging.

[0069] The time interval value ΔT2 can be adjusted according to actual conditions, such as by remote setting by technicians based on experience, or adjusted according to road conditions. For example, on flat roads, the time interval value can be appropriately increased, and on curved roads, inclined roads with a slope greater than a preset slope value, or congested roads, the time interval value can be appropriately reduced to minimize the number of fluctuations in the output power of the fuel cell and reduce the switching frequency. In this way, by adjusting the energy exchange between the power battery and the supercapacitor with the goal of minimizing the number of fluctuations in the output power of the fuel cell, the frequent power changes of the fuel cell can be reduced and its service life can be extended.

[0070] In summary, the power optimization method for fuel cell commercial vehicles predicts the SOC fluctuation state of the power battery and adjusts the energy exchange between the power battery and the supercapacitor in a timely manner. It optimizes power distribution with the goal of minimizing the number of fluctuations in the fuel cell output power. It can avoid the instability of the fuel cell power output caused by the SOC fluctuation near the critical value, thereby reducing the frequent power changes of the fuel cell and extending its service life.

[0071] In one embodiment, if Figure 2 As shown, in step S2, predicting the SOC fluctuation state of the power battery includes the following steps:

[0072] S21, obtaining the estimated working state of the load motor and the estimated working condition of the current road;

[0073] S22, predicting the SOC fluctuation state of the power battery according to the budgeted working state and the budgeted operating condition.

[0074] Preferably, in step S21, Figure 3 As shown, the specific method for obtaining the estimated working state of the load motor and the estimated working condition of the current road includes the following steps:

[0075] S211, according to formula Peng f(t) = [α·Load(t) + β·RPM(t) + γ]·K T ·K H Obtain the budget working state of the load motor.

[0076] S212. According to the formula Obtain the budget working condition of the current road.

[0077] where Load represents the real-time load signal, RPM represents the motor speed, α and β represent the weight coefficients of the real-time load signal and the motor speed respectively, γ represents the bias constant, K T 、K H respectively represent the temperature correction coefficient and the altitude correction coefficient, m represents the total vehicle mass, g represents the acceleration due to gravity, μ represents the rolling resistance coefficient, θ represents the road gradient, v represents the vehicle speed, ρ, C d 、A respectively represent the air density, the drag coefficient and the frontal area.

[0078] The real-time load signal can be directly obtained through the throttle pedal opening or the hydraulic system pressure signal. For example, signals such as the pedal position sensor and the hydraulic pump pressure sensor are collected through the in-vehicle CAN bus, which reflects the driver's torque demand for the engine. For example, when accelerating, the opening increases and the load rises; when braking or idling, the load decreases. The motor speed is the number of revolutions per minute of the motor, with the unit of r / min, and can be monitored in real time through the crankshaft position sensor or the flywheel speed sensor. It characterizes the dynamic working frequency of the engine and directly affects the power output efficiency and fuel consumption. The weight coefficients of the real-time load signal and the motor speed can be calibrated through historical data. For example, based on experimental data (such as bench tests or road tests), the optimal values are fitted using multiple linear regression or the least squares method, etc. The bias constant is used to compensate for the unmodeled static power losses (such as mechanical friction and accessory power consumption), and can be determined through experiments under the no-load and idle conditions of the engine.

[0079] The temperature correction coefficient K T = 1 - λ·(T env - T base ), where T env 、T base respectively represent the real-time ambient temperature and the reference ambient temperature (usually taken as 25 °C), λ represents the temperature attenuation coefficient, and the range can be set to 0.005 - 0.015 / °C. The altitude correction coefficient K H = 1 - κ(H / 1000), H represents the altitude, and κ represents the altitude attenuation coefficient, and the range can be set to 0.08 - 0.12.

[0080] An increase in ambient temperature will lead to a decrease in the power of the motor. High temperature reduces the heat dissipation efficiency and affects the thermal efficiency. With every increase in altitude, the air density decreases, which in turn leads to power attenuation. According to the formula P eng (t) = [α·Load(t) + β·RPM(t) + γ]·K T ·K H Obtain the budget working state of the load motor while considering temperature and altitude. Using product correction instead of superposition correction is more in line with the actual non-linear effect. For the real-time ambient temperature and altitude, they can be obtained in real time through in-vehicle temperature sensors and barometric pressure sensors, and the real-time parameters are updated every 10 seconds.

[0081] The prediction of the budget working state of the load motor takes into account environmental factors (including ambient temperature and altitude), significantly improving the prediction accuracy of the motor power under complex operating conditions of commercial vehicles. In addition, the formula P eng (t) = [α·Load(t) + β·RPM(t) + γ]·K T ·K H The variable parameters in it include real-time load signals, motor speed, and environmental factors. The overall calculation model is relatively simple. Compared with complex neural network prediction models, it can reduce the calculation cost and improve the response speed.

[0082] For the road conditions ahead, the road conditions ahead (gradient and speed) can be obtained through in-vehicle sensors (such as cameras, GPS), and the budget operating conditions of the current road are calculated. The rolling resistance coefficient is dimensionless, which can be understood as the friction coefficient between the tire and the road surface. The aerodynamic drag coefficient is dimensionless, and the vehicle frontal area is the projected area of the vehicle perpendicular to the driving direction.

[0083] respectively represent the gradient and the rolling resistance term and the aerodynamic drag term. sinθ represents the gravitational component caused by the gradient. When the vehicle goes uphill, it needs to overcome gravity to do work, and when going downhill, energy can be recovered. μcosθ represents the frictional loss between the tire and the road surface, which is proportional to the vehicle speed. The cube of the speed v 3 indicates that the influence of air resistance on energy demand increases significantly at high speeds. For the rolling resistance coefficient and the aerodynamic drag coefficient, they can both be calibrated through historical data to improve the prediction accuracy.

[0084] Preferably, as Figure 4 shown, the specific method for predicting the SOC fluctuation state of the power battery according to the budget working state and the budget operating conditions includes the following steps:

[0085] S221, construct an SOC change rate equation

[0086] S222, through the Kalman filter Real-time correction of the SOC prediction error;

[0087] Where Q represents the rated capacity of the power battery, η ch and η dis represent the charging efficiency and the discharging efficiency respectively, P charge (t) represents the regenerative braking feedback power, represents the optimal estimated value of SOC at the current time t, the prior predicted value of SOC at time t based on the optimal estimate at time t-1, K t represents the Kalman gain, SOC meas,t represents the actual measured SOC value at the current time t.

[0088] The actual measured SOC value at the current time t can be obtained from the raw data acquired by the battery voltage / current sensor. The optimal estimated value of SOC at the current time t can be understood as the SOC correction result after fusing the predicted value and the measured value, with the minimum mean square error.

[0089] For the Kalman gain Where P k|K-1 and R k represent the prediction error covariance and the measurement noise covariance respectively. The state vector x of the Kalman filter k = [SOC, OCV, polarization voltage] T , where OCV represents the open-circuit voltage of the power battery. The state vector only retains three core state variables, SOC, OCV, and polarization voltage, which can reduce the computational amount compared with the traditional EKF (usually including SOC, polarization voltage, temperature, aging factor, etc.).

[0090] The prediction of the SOC fluctuation state of the power battery integrates multi-source signals such as engine load, road gradient, and battery voltage, which can improve the prediction robustness. The SOC change rate equation and the Kalman filter only retain the core state variables (SOC and voltage), which can reduce the computational complexity. That is to say, this embodiment significantly reduces the computational complexity while ensuring the prediction accuracy, and is applicable to the complex working condition requirements of commercial vehicles.

[0091] In one embodiment, as Figure 6 shown, the power optimization method for the fuel cell commercial vehicle further includes the following steps:

[0092] S3. Obtain the real-time power of the super capacitor;

[0093] S4. If the real-time power is greater than the first preset multiple of the rated capacitance of the super capacitor, charge the power battery through the super capacitor to reduce the real-time power to the standard preset multiple of the rated capacitance of the super capacitor;

[0094] S5. If the real-time power is less than the second preset multiple of the rated capacitance of the super capacitor, charge the super capacitor with the power battery to increase the real-time power to the standard preset multiple of the rated capacitance of the super capacitor.

[0095] Among them, the first preset multiple > the standard preset multiple > the second preset multiple, and both the first preset multiple and the second preset multiple are within the range of (0, 1). The first preset multiple can be set to 0.55, the second preset multiple can be set to 0.45, and the standard preset multiple can be set to 0.5.

[0096] For a super capacitor, if it is desired to implement the capacitance adjustment and compensation function, the super capacitor needs to be in an adjustable state. To have the function of increasing the power of the power battery and reducing the power of the power battery, the super capacitor needs to maintain a medium power state - the power of the super capacitor is 0.5. Detect the power of the super capacitor through the VCU. When the power of the super capacitor is greater than 0.55, charge the power battery with the super capacitor to reduce the power of the super capacitor to 0.5; when the power of the super capacitor is less than 0.45, charge the super capacitor with the power battery to increase the power of the super capacitor to 0.5.

[0097] In this way, by setting the first preset multiple, the standard preset multiple, and the second preset multiple, the adjustment and compensation function of the super capacitor can be better realized.

[0098] In one embodiment, as Figure 7 shown, the specific method for adjusting the power output of the fuel cell in different SOC states according to the SOC state of the power battery includes the following steps:

[0099] S6. When the SOC state of the power battery is in the first state interval, adjust the power output of the fuel cell to the first power interval.

[0100] S7. When the SOC state of the power battery is in the second state interval, adjust the power output of the fuel cell to the second power interval.

[0101] S8. When the SOC state of the power battery is in the third state interval, adjust the power output of the fuel cell to the third power interval.

[0102] Among them, the lower limit value of the first state interval is greater than the upper limit value of the second state interval, the lower limit value of the second state interval is greater than the upper limit value of the third state interval, the upper limit value of the first power interval is less than the lower limit value of the second power interval, and the upper limit value of the second power interval is less than the lower limit value of the third power interval.

[0103] Specifically, the output power of the fuel cell is divided into three ranges: large, medium, and small, and the SOC control strategy is adopted for power distribution. According to the SOC state of the power battery, the fuel cell adjusts its power output at different SOC states: when the SOC of the power battery is high, the fuel cell outputs a small power; when the SOC is medium, the fuel cell outputs a medium power; when the SOC is low, the fuel cell outputs a high power. For example, the low, medium, and high output powers of the fuel cell are set to 40kW, 120kW, and 240kW respectively. Correspondingly, the first power range, the second power range, and the third power range are set to (20, 60), (60, 180), and (180, 300) respectively, and the first state range, the second state range, and the third state range corresponding to the SOC state (state of charge of the battery) are set to (0.7 - 0.9), (0.3 - 0.7), and (0.1, 0.3) respectively. When the SOC of the power battery is high (such as SOC = 0.8 or SOC = 0.85), the fuel cell outputs a small power (40kW); when the SOC is at a medium level (such as SOC = 0.4 or SOC = 0.6), the fuel cell outputs a power of 120kW; when the SOC is low (such as SOC = 0.2 or SOC = 0.25), the fuel cell provides the maximum power (240kW). This division of power ranges and the SOC control strategy can effectively optimize power distribution, reduce the fluctuation of the fuel cell power output, and improve the stability and efficiency of the system.

[0104] For the specific upper and lower limits of the first state range, the second state range, the third state range, the first power range, the second power range, and the third power range, they can be set and adjusted according to specific situations, which will not be elaborated here.

[0105] By dividing the output power of the fuel cell into high, medium, and low power ranges and introducing a super capacitor for intelligent adjustment, the problem of fuel cell power fluctuation is solved, the stability of the system is effectively improved, and the service life of the fuel cell is extended.

[0106] An embodiment of the present invention further provides a power optimization system for a fuel cell commercial vehicle based on a super capacitor, which is used to implement the power optimization method of the fuel cell commercial vehicle, as Figure 8 shown, which includes a power adjustment module and a power exchange module.

[0107] The power adjustment module is used to supply power to the load motor jointly by the fuel cell and the power battery, and adjusts the power output of the fuel cell at different SOC states according to the SOC state of the power battery; the power exchange module is used to predict the SOC fluctuation state of the power battery, and takes minimizing the number of fuel cell output power fluctuations as the goal to adjust the energy exchange between the power battery and the super capacitor.

[0108] Specifically, the regulation function of the super capacitor is based on global optimization. The VCU adopts optimal control principles (such as dynamic programming and genetic algorithms) to optimize the control strategy and reduce the number of switching times of the fuel cell power range in a fluctuating driving environment. By precisely controlling the power regulation of the super capacitor for the power battery and the regulation time, the intelligent regulation function of the super capacitor is exerted, thereby reducing the fluctuation of vehicle power distribution.

[0109] Regarding the regulation time, it can be understood as a variable time interval value ΔT2 based on global optimality. For example, assume that the current time is T0. If, based on the predicted SOC fluctuation state of the power battery, within the future time T0 + ΔT2, the power battery power is lower than the low critical value of 40% or even lower, such as 30%, etc., then the super capacitor compensates the power battery. Here, the critical difference refers to the gap between the high critical value and the low critical value, which is used to ensure the flexibility of power regulation and avoid overly frequent charging and discharging.

[0110] The time interval value ΔT2 can be adjusted according to actual situations. For example, it can be remotely set by technicians based on experience, or adjusted according to road conditions. For example, on a flat road condition, the time interval value can be appropriately increased; on a curved road, an inclined road surface with a slope greater than the preset slope value, or a congested road, the time interval value can be appropriately reduced to minimize the number of fluctuations of the fuel cell output power and reduce the switching frequency. In this way, by aiming to minimize the number of fluctuations of the fuel cell output power and adjusting the energy exchange between the power battery and the super capacitor, the frequent power changes of the fuel cell can be reduced, and its service life can be extended.

[0111] Preferably, as Figure 9 shown, the power exchange module includes a prediction unit and an SOC acquisition unit.

[0112] The prediction unit is used to obtain the budget working state of the load motor and the budget working condition of the current road; the SOC acquisition unit is used to predict the SOC fluctuation state of the power battery according to the budget working state and the budget working condition.

[0113] The SOC acquisition unit predicts the SOC fluctuation state of the power battery according to the SOC change rate equation and the Kalman filter ;

[0114] wherein, Load represents the real-time load signal, RPM represents the motor speed, α and β represent the weight coefficients of the real-time load signal and the motor speed, γ represents the bias constant, K T 、K Hrespectively represent the temperature correction coefficient and the altitude correction coefficient, m represents the total vehicle mass, g represents the acceleration due to gravity, μ represents the rolling resistance coefficient, θ represents the road gradient, v represents the vehicle speed, ρ, C d , A respectively represent the air density, the drag coefficient and the frontal area, Q represents the rated capacity of the power battery, η ch , η dis respectively represent the charging efficiency and the discharging efficiency, P charge (t) represents the regenerative braking feedback power, represents the optimal estimated value of the SOC at the current moment t, the prior predicted value of the SOC at moment t based on the optimal estimate at moment t - 1, K t represents the Kalman gain, SOC meas,t represents the actual measured SOC value at the current moment t.

[0115] The power optimization system of the fuel cell commercial vehicle predicts the SOC fluctuation state of the power battery, adjusts the energy exchange between the power battery and the super capacitor in a timely manner, optimizes the power distribution with the goal of minimizing the number of fluctuations of the fuel cell output power, and can avoid the instability of the fuel cell power output caused by the fluctuation of the SOC near the critical value, thereby reducing the frequent power change of the fuel cell and prolonging its service life.

[0116] In one embodiment, as Figure 10 shown, the power optimization system of the fuel cell commercial vehicle based on the super capacitor includes a DC / DC converter, an inverter, a fuel cell, a power battery, a super capacitor, a VCU (Vehicle Control Unit) controller, a BMS (Battery Management System), and a load motor.

[0117] The fuel cell and the power battery jointly provide power for the load motor, and a combination of a high-power fuel cell and a low-power power battery is adopted. The high-power fuel cell directly supplies power to the inverter and supplies power to the load motor through the inverter, while the low-power power battery first meets the voltage requirement through the DC / DC converter and then supplies power to the load motor through the inverter. Among them, the DC / DC converter is responsible for the energy transmission and regulation between different power systems.

[0118] The super capacitor has the characteristics of low energy density and high power density, and can release a large amount of energy in a short time. Its main function is to adjust the SOC of the power battery and does not participate in the power output of the vehicle. The super capacitor is controlled by the VCU controller to adjust the SOC of the power battery to optimize the overall system performance.

[0119] The VCU controller adjusts the power output range of the fuel cell based on the SOC control strategy. At the same time, the VCU minimizes the switching times of the fuel cell power range through global optimization algorithms (such as dynamic programming and genetic algorithms), intelligently regulates the energy exchange between the supercapacitor and the power battery, optimizes the power distribution, and improves the system stability.

[0120] The system determines the supplementary charge signal in real time through the VCU controller and dynamically adjusts the energy exchange between the supercapacitor and the power battery. The VCU controller monitors the state of the vehicle load motor and predicts the future change of the power battery SOC in combination with the driving conditions. When the SOC approaches the critical value, the VCU enters the pre-supplementary adjustment state, and judges whether it is necessary to adjust the SOC of the battery in combination with the power status of the supercapacitor to ensure the stable output of the fuel cell.

[0121] The power optimization system of the fuel cell commercial vehicle simulates different driving conditions, collects the output data of the fuel cell, power battery, and supercapacitor in real time, and analyzes the performance and characteristics of the system under various conditions to optimize the system design.

[0122] As Figure 10 shown, the fuel cell, power battery, load motor, inverter, and DC / DC converter are used as the power drive module. In the power drive module, the fuel cell and the power battery are used as power sources to make the load motor operate and drive the whole vehicle. The load motor receives the actual power transmitted from the two power sources of the fuel cell and the power battery, and outputs the power demand in comparison with the input of the simulated working condition. The high-power fuel cell can provide a high enough and stable voltage to meet the requirements of the inverter and the motor. The low-power power battery needs to be boosted by the DC / DC converter to meet the voltage requirements. The inverter is distributed between the battery and the motor. The inverter is responsible for converting the direct current output by the battery into the three-phase alternating current required by the motor, and adjusting the frequency and voltage to control the speed and torque of the motor.

[0123] The BMS and the VCU controller are used as the SOC control strategy module. The power optimization system adopts the SOC control strategy, that is, mainly adjusts the output power distribution of the fuel cell and the power battery according to the remaining power state SOC of the power battery. The VCU controller is the core of this module. The VCU extracts the SOC of the power battery adopted by the BMS and combines the power demand feedback signal to achieve a relatively complete power distribution.

[0124] The supercapacitor, DC / DC converter, and VCU controller are used as the capacitor supplementary control module. The capacitor supplementary control is an optimization based on the SOC control strategy, and is a solution to the multiple jumps of the fuel cell working power range due to the fluctuating state of the SOC under multi-fluctuating road conditions.

[0125] The VCU controller serves as the core of the processing. The VCU controller receives the budgeted operating state from the load motor and the budgeted operating conditions from the simulated condition input, combines with the vehicle's own parameters, calculates the consumption state of the power battery's power to obtain the fluctuation state of the power battery's SOC. Combining the SOC fluctuation state with the high and low limits of SOC in the SOC control strategy, predicts whether the operating range of the fuel cell will be in a fluctuating state, and combines the predicted SOC value and the supercapacitor's power value to input a supplementary power signal to the supercapacitor.

[0126] The supercapacitor receives the supplementary power signal and exchanges power with the power battery through a DC / DC converter, so that the SOC of the power battery is in a relatively stable range, reducing the switching of the operating power range of the fuel cell.

[0127] The power optimization system also includes an adjustment module. For the adjustment module, its main function is to put the supercapacitor in a ready state, that is, to make the capacitance power level of the supercapacitor 0.5 (i.e., 50%).

[0128] Specifically, for the supercapacitor, if you want to achieve the capacitance supplementary function, the supercapacitor needs to be in an adjustable supplementary state. The supercapacitor needs to have the function of increasing and decreasing the power of the power battery, so it needs to maintain a medium power state - the supercapacitor's power is 0.5.

[0129] When the supercapacitor's power is relatively high (for example, the power is greater than 0.5), its main function is to provide electrical energy for the power battery, reducing the power loss of the power battery. When the power is relatively low (for example, the power is less than 0.45), the supercapacitor will receive power supplementation from the power battery to keep its power within a reasonable range for subsequent adjustment and use. To optimize power distribution and extend the system life, the power state of the supercapacitor is usually maintained at about 0.5, that is, the power is in a medium charging state, which can not only ensure the energy balance of the battery but also provide sufficient power support.

[0130] The function realized by the adjustment module is to detect the power of the supercapacitor through the VCU controller. When the power of the supercapacitor is greater than 0.55, the supercapacitor charges the power battery, reducing the power of the supercapacitor to 0.5; when the power of the supercapacitor is less than 0.45, the power battery charges the supercapacitor, increasing the power of the supercapacitor to 0.5.

[0131] Among them, as Figure 11As shown, the power exchange module, as the decision-making module, has a higher priority than the adjustment module. The idea of the power exchange module is to first combine the road conditions and the vehicle operating conditions to predict the fluctuation of the power battery SOC, and determine whether the SOC fluctuation exceeds the SOC limit. If the SOC fluctuation exceeds the limit, then determine whether the power contained in the super capacitor can compensate for the overflow value of the power battery SOC. If it can, the super capacitor will be used for compensation. The selection of ΔT1 and ΔT2 is based on global optimization, and the time period is determined with the goal of minimizing the switching times of the fuel cell operating power range. T0 is the initial time point when the statistics start, and ΔT1 is the time increment after starting from T0.

[0132] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0133] The above-described embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent should be subject to the appended claims.

Claims

1. A power optimization method for a fuel cell commercial vehicle based on a supercapacitor, characterized in that The power optimization method for the fuel cell commercial vehicle includes the following steps: The fuel cell and the power battery jointly supply power to the load motor, and the power output of the fuel cell under different SOC states is adjusted according to the SOC state of the power battery; Predict the SOC fluctuation state of the power battery, and adjust the energy exchange between the power battery and the super capacitor with the goal of minimizing the number of fluctuations in the fuel cell output power.

2. The power optimization method for a fuel cell commercial vehicle based on a supercapacitor according to claim 1, wherein Predicting the SOC fluctuation state of the power battery includes the following steps: Obtain the budget working state of the load motor and the budget working condition of the current road; Predict the SOC fluctuation state of the power battery according to the budget working state and the budget working condition.

3. The power optimization method for a fuel cell commercial vehicle based on a supercapacitor according to claim 2, characterized in that, Adjusting the energy exchange between the power battery and the super capacitor includes the following steps: According to the SOC fluctuation state of the power battery, predict whether the power of the power battery is higher than the first critical value. If so, judge whether the power of the super capacitor is greater than the critical difference of the power battery. If so, charge the super capacitor through the power battery; According to the SOC fluctuation state of the power battery, predict whether the power of the power battery is lower than the second critical value. If so, judge whether the power of the super capacitor is greater than the critical difference of the power battery. If so, charge the power battery through the super capacitor; Wherein, the first critical value is greater than the second critical value.

4. The power optimization method for a fuel cell commercial vehicle based on a super capacitor according to claim 3, wherein The power optimization method for the fuel cell commercial vehicle further includes the following steps: Obtain the real-time power of the super capacitor; If the real-time power is greater than the first preset multiple of the rated capacitance of the super capacitor, charge the power battery through the super capacitor to reduce the real-time power to the standard preset multiple of the rated capacitance of the super capacitor; If the real-time power is less than the second preset multiple of the rated capacitance of the super capacitor, charge the super capacitor through the power battery to increase the real-time power to the standard preset multiple of the rated capacitance of the super capacitor; Wherein, the first preset multiple > the standard preset multiple > the second preset multiple, and both the first preset multiple and the second preset multiple are within the range of (0, 1).

5. The power optimization method for a fuel cell commercial vehicle based on a supercapacitor according to claim 4, wherein The specific method for adjusting the power output of the fuel cell under different SOC states according to the SOC state of the power battery includes the following steps: When the SOC state of the power battery is in the first state interval, adjust the power output of the fuel cell to the first power interval; When the SOC state of the power battery is in the second state interval, adjust the power output of the fuel cell to the second power interval; When the SOC state of the power battery is in the third state interval, adjust the power output of the fuel cell to the third power interval; Wherein, the lower limit value of the first state interval is greater than the upper limit value of the second state interval, the lower limit value of the second state interval is greater than the upper limit value of the third state interval, the upper limit value of the first power interval is less than the lower limit value of the second power interval, and the upper limit value of the second power interval is less than the lower limit value of the third power interval.

6. The power optimization method for a fuel cell commercial vehicle based on a supercapacitor according to claim 5, wherein The specific method for obtaining the budget working state of the load motor and the budget working condition of the current road includes the following steps: According to the formula P eng (t) = [α·Load(t) + β·RPM(t) + γ]·K T ·K H obtain the budget working state of the load motor; According to the formula Obtain the budget working condition of the current road; Among them, Load represents the real-time load signal, RPM represents the motor speed, α and β represent the weight coefficients of the real-time load signal and the motor speed respectively, γ represents the bias constant, K T and K H represent the temperature correction coefficient and the altitude correction coefficient respectively, m represents the total vehicle mass, g represents the acceleration due to gravity, μ represents the rolling resistance coefficient, θ represents the road slope, v represents the vehicle speed, ρ, C d and A represent the air density, the drag coefficient and the frontal area respectively.

7. The power optimization method for a fuel cell commercial vehicle based on a super capacitor according to claim 6, wherein The specific method for predicting the SOC fluctuation state of the power battery according to the budget working state and the budget working condition includes the following steps: Construct the SOC change rate equation Through a Kalman filter Real-time correction of the SOC prediction error; Among them, Q represents the rated capacity of the power battery, η ch and η dis represent the charging efficiency and the discharging efficiency respectively, P charge (t) represents the regenerative braking feedback power, represents the optimal estimated value of the SOC at the current moment t, the prior predicted value of the SOC at the moment t based on the optimal estimate at the moment t - 1, K t represents the Kalman gain, SOC meas,t represents the actual measured SOC value at the current moment t.

8. A power optimization system for a fuel cell commercial vehicle based on a super capacitor, which is used to implement the power optimization method for a fuel cell commercial vehicle according to any one of claims 1-7, characterized in that It includes: A power adjustment module, which is used to supply power to the load motor jointly by the fuel cell and the power battery, and adjust the power output of the fuel cell under different SOC states according to the SOC state of the power battery; A power exchange module, which is used to predict the SOC fluctuation state of the power battery and adjust the energy exchange between the power battery and the super capacitor with the goal of minimizing the number of fluctuations in the output power of the fuel cell.

9. The power optimization system for a fuel cell commercial vehicle based on a supercapacitor according to claim 8, characterized in that, The power exchange module includes: A prediction unit, which is used to obtain the budget working state of the load motor and the budget working condition of the current road; An SOC acquisition unit, which is used to predict the SOC fluctuation state of the power battery according to the budget working state and the budget working condition.

10. The power optimization system for a fuel cell commercial vehicle based on a super capacitor as described in claim 9, characterized in that, The SOC acquisition unit predicts the SOC fluctuation state of the power battery according to the SOC change rate equation and the Kalman filter ; Among them, Load represents the real-time load signal, RPM represents the motor speed, α and β represent the weight coefficients of the real-time load signal and the motor speed respectively, γ represents the bias constant, K T , K H represent the temperature correction coefficient and the altitude correction coefficient respectively, m represents the total vehicle mass, g represents the acceleration due to gravity, μ represents the rolling resistance coefficient, θ represents the road slope, v represents the vehicle speed, ρ, C d , A represent the air density, the drag coefficient and the frontal area respectively, Q represents the rated capacity of the power battery, η ch , η dis represent the charging efficiency and the discharging efficiency respectively, P charge (t) represents the regenerative braking feedback power, represents the optimal estimated value of SOC at the current time t, the prior predicted value of SOC at time t based on the optimal estimate at time t-1, K t represents the Kalman gain, SOC meas,t represents the actual measured SOC value at the current time t.

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