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

Abstract

The application relates to the technical field of power supply and distribution systems, and provides a fuel cell commercial vehicle power optimization method and system based on a super capacitor, wherein the fuel cell commercial vehicle power optimization method comprises the following steps: jointly supplying power to a load motor by a fuel cell and a power battery, adjusting power output of the fuel cell under different SOC states according to an SOC state of the power battery; and predicting an SOC fluctuation state of the power battery, and adjusting energy exchange between the power battery and the super capacitor with the target of minimizing the number of fuel cell output power fluctuation times. By predicting the SOC fluctuation state of the power battery and timely adjusting the energy exchange between the power battery and the super capacitor, the application optimizes power distribution with the target of minimizing the number of fuel cell output power fluctuation times, can avoid instability of fuel cell power output caused by SOC fluctuation near a critical value, and thus reduces frequent power changes of the fuel cell and prolongs the service life of the fuel cell.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power supply systems, in particular to a fuel cell commercial vehicle power optimization method and system based on supercapacitors. BACKGROUND

[0002] Current fuel cell commercial vehicle power systems usually use a combination of fuel cells and power batteries, and perform system power distribution based on SOC control strategies. The power output of the fuel cell is usually divided into three power intervals: large, medium and small, and the SOC value is used as the switching standard.

[0003] SOC control strategies can reduce fuel cell power fluctuations to some extent, but in driving conditions, when the SOC value approaches the switching standard, the fuel cell power may still fluctuate greatly, especially in the case of frequent switching between two or more power intervals. This fluctuation will affect the output stability of the fuel cell and may shorten its service life. SUMMARY

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

[0005] The fuel cell commercial vehicle power optimization method based on supercapacitors includes the following steps:

[0006] The fuel cell and the power battery are combined to 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;

[0007] The SOC fluctuation state of the power battery is predicted, and the energy exchange between the power battery and the supercapacitor is adjusted to minimize the number of fuel cell output power fluctuations.

[0008] The fuel cell commercial vehicle power optimization method 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 by minimizing the number of fuel cell output power fluctuations, which can avoid the instability of fuel cell power output caused by SOC fluctuations near the critical value, thereby reducing frequent power changes 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] Obtain the budget working state of the load motor and the budget working condition of the current road;

[0011] According to the budget working state and the budget working condition, the SOC fluctuation state of the power battery is predicted.

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

[0013] According to the SOC fluctuation state of the power battery, it is predicted whether the power of the power battery is higher than a first critical value, if yes, it is judged whether the power of the super capacitor is greater than a critical difference value of the power battery, if yes, the super capacitor is charged by the power battery;

[0014] According to the SOC fluctuation state of the power battery, it is predicted whether the power of the power battery is lower than a second critical value, if yes, it is judged whether the power of the super capacitor is greater than a critical difference value of the power battery, if yes, the power battery is charged by 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 comprises the following steps:

[0017] The real-time power of the super capacitor is obtained;

[0018] If the real-time power is greater than a first preset multiple of the rated capacity of the super capacitor, the power battery is charged by the super capacitor, so that the real-time power is reduced to a standard preset multiple of the rated capacity of the super capacitor;

[0019] If the real-time power is less than a second preset multiple of the rated capacity of the super capacitor, the super capacitor is charged by the power battery, so that the real-time power is increased to a standard preset multiple of the rated capacity of the super capacitor;

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

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

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

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

[0024] adjusting the power output of the fuel cell to a third power interval when the SOC state of the power battery is in a third state interval;

[0025] 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.

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

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

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

[0029] wherein Load represents a real-time load signal, RPM represents a motor speed, α and β represent weight coefficients of the real-time load signal and the motor speed, γ represents a bias constant, K T , K H respectively represent temperature correction coefficients and altitude correction coefficients, m represents a total mass of the vehicle, g represents a gravitational acceleration, μ represents a rolling resistance coefficient, θ represents a road slope, v represents a vehicle speed, ρ, C d , and A respectively represent air density, wind resistance coefficient, and windward 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 comprises the following steps:

[0031] constructing a SOC change rate equation

[0032] correcting the SOC prediction error in real time through a Kalman filter

[0033] wherein Q represents a rated capacity of the power battery, η ch , and η dis respectively represent charging efficiency and discharging efficiency, P charge (t) represents a regenerative braking feedback power, represents an optimal estimation value of the SOC at the current time t, predicting the SOC prior value at time t on the basis of the optimal estimation at time t-1, and K​t denotes the Kalman gain, SOC meas,t denotes the actual measured SOC value at the current time t.

[0034] The fuel cell commercial vehicle power optimization system based on super capacitor is used to realize the fuel cell commercial vehicle power optimization method, and comprises:

[0035] A power adjustment module is configured to supply power to a load motor jointly by a fuel cell and a power battery, and to adjust power output of the fuel cell at different SOC states according to an SOC state of the power battery.

[0036] An electric quantity exchange module is configured to predict an SOC fluctuation state of the power battery, and to adjust energy exchange between the power battery and a super capacitor with the aim of minimizing the number of fuel cell output power fluctuations.

[0037] Preferably, the electric quantity exchange module comprises:

[0038] A prediction unit is configured to obtain a budget working state of the load motor and a budget working condition of a current road.

[0039] An SOC acquisition unit is configured 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 an SOC change rate equation and a Kalman filter

[0041] wherein Load represents a real-time load signal, RPM represents a motor speed, α and β represent weight coefficients of the real-time load signal and the motor speed, γ represents a bias constant, K T , K H respectively represent a temperature correction coefficient and an altitude correction coefficient, m represents a total mass of the vehicle, g represents a gravitational acceleration, μ represents a rolling resistance coefficient, θ represents a road slope, v represents a vehicle speed, ρ, C d , and A respectively represent air density, air resistance coefficient, and windward area, Q represents a rated capacity of the power battery, η ch , η dis respectively represent charging efficiency and discharging efficiency, P charge (t) represents a regenerative braking feedback power, denotes an optimal estimation value of the SOC at the current time t, predicts a priori prediction value of the SOC at the time t based on optimal estimation at the time t-1, K t denotes the Kalman gain, SOC meas,t ​This represents the actual measured SOC value at the current time t. Attached Figure Description

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

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

[0044] Figure 2 This is a flowchart illustrating a specific method for predicting the SOC fluctuation state of the power battery in one embodiment of the present invention.

[0045] Figure 3 This is a flowchart illustrating a specific method for obtaining the budgeted operating status of the load motor and the current budgeted operating conditions of the road in one embodiment of the present invention.

[0046] Figure 4 This is a flowchart illustrating a specific method for predicting the SOC fluctuation state of the power battery in one embodiment of the present invention.

[0047] Figure 5 This is a flowchart illustrating a specific method for adjusting the energy exchange mode between the power battery and the supercapacitor in one embodiment of the present invention.

[0048] Figure 6 This is a flowchart illustrating a method for optimizing the power of fuel cell commercial vehicles according to another embodiment of the present invention;

[0049] Figure 7 This is a flowchart illustrating a specific method for adjusting the power output of the fuel cell under different SOC states in one embodiment of the present invention.

[0050] Figure 8 This is a schematic diagram of the overall structure of a fuel cell commercial vehicle power optimization system according to one embodiment of the present invention;

[0051] Figure 9 This is a functional structure diagram of the power exchange module according to one embodiment of the present invention;

[0052] Figure 10 This is a schematic diagram of the structure of a fuel cell commercial vehicle power optimization system according to another embodiment of the present invention. Figure 1 ;

[0053] Figure 11 This is a schematic diagram of the structure of a fuel cell commercial vehicle power optimization system according to another embodiment of the present invention. Figure 2 . Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of protection of the invention.

[0055] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0057] In this invention, "first" and "second" do not represent a specific quantity or order, but are merely used to distinguish names.

[0058] like Figure 1 As shown, an embodiment of the present invention provides a power optimization method for commercial vehicles based on supercapacitor fuel cells, comprising the following steps:

[0059] S1, the combined fuel cell and power battery supply power to the load motor, 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 oxidant (usually oxygen) into electrical energy through an electrochemical reaction. It does not require a combustion process, therefore its energy conversion efficiency is high, and its emissions are mainly water vapor, making it very environmentally friendly. The core component of a fuel cell is the electrolyte membrane, which only allows the passage of specific ions, thus achieving the goal of directly converting chemical energy into electrical energy. A power battery is a power source that provides power to tools, often referring to the batteries that power electric vehicles, electric trains, electric bicycles, and golf carts, including ternary lithium batteries, lithium iron phosphate batteries, lithium cobalt oxide batteries, and nickel-metal hydride batteries.

[0061] In the embodiment, the power optimization method is based on an existing fuel cell vehicle power system, and the power distribution is managed and optimized 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, and the super capacitor adjusts the SOC of the power battery to optimize the power distribution between the fuel cell and the power battery, and reduces the power interval jump of the fuel cell.

[0062] S2, predicting the SOC fluctuation state of the power battery, adjusting the energy exchange between the power battery and the super capacitor to minimize the number of fuel cell output power fluctuations.

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

[0064] S23, according to the SOC fluctuation state of the power battery, predicting whether the power of the power battery is higher than a first critical value, if yes, judging whether the power of the super capacitor is greater than a critical difference value of the power battery, if yes, charging the super capacitor by the power battery;

[0065] S24, according to the SOC fluctuation state of the power battery, predicting whether the power of the power battery is lower than a second critical value, if yes, judging whether the power of the super capacitor is greater than a critical difference value of the power battery, if yes, charging the power battery by the super capacitor;

[0066] Wherein, 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] By using the combination of high-power fuel cell, low-power power battery and super capacitor, the fuel cell and power battery provide power output according to the SOC control strategy, and the transient power demand of acceleration, starting and braking energy recovery is mainly provided by the power battery. The super capacitor is used to adjust and supplement the SOC of the power battery, that is, the SOC fluctuation state of the power battery is predicted based on a neural network, and the energy exchange between the power battery and the super capacitor is adjusted to minimize the number of fuel cell output power fluctuations.

[0068] ​Specifically, the method for minimizing the number of fuel cell output power fluctuations includes setting a variable time interval value ΔT2 based on a global optimum, and then calculating a difference power value and compensating the power battery with the super capacitor according to the predicted SOC fluctuation state of the power battery, thereby reducing the frequent adjustment of the fuel cell due to sudden load fluctuations. For example, assuming that the current time is T0, if the power battery is compensated by the super capacitor based on the predicted SOC fluctuation state of the power battery, the power battery power is lower than the low critical value 0.4 or lower 0.3, etc. within the future time T0+ΔT2. The critical difference value refers to the difference between the high critical value and the low critical value, which is used to ensure the flexibility of power adjustment and avoid excessive frequent charging and discharging.

[0069] The time interval value ΔT2 can be adjusted according to actual conditions, such as being remotely set by a technician according to experience, or being adjusted according to road conditions, such as appropriately increasing the time interval value in flat road conditions, or appropriately reducing the time interval value in curved roads, inclined road surfaces with a slope greater than a preset slope value, or congested roads, so as to reduce the number of fuel cell output power fluctuations and reduce the switching frequency as much as possible. In this way, by adjusting the energy exchange between the power battery and the super capacitor to minimize the number of fuel cell output power fluctuations, the frequent power changes of the fuel cell can be reduced, and the service life of the fuel cell can be prolonged.

[0070] In summary, the fuel cell commercial vehicle power optimization method 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, and optimizes the power distribution by minimizing the number of fuel cell output power fluctuations. The method can avoid the instability of fuel cell power output caused by the fluctuation of SOC near the critical value, thereby reducing the frequent power changes of the fuel cell and prolonging the service life of the fuel cell.

[0071] In one embodiment, as shown in Figure 2 the SOC fluctuation state of the power battery includes the following steps:

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

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

[0074] Preferably, in step S21, as shown in Figure 3 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:

[0075] S211, calculating the load motor power P according to the formula P = P0+ P1+ P2+ P3+ P4+ P5+ P6+ P7+ P8+ P9+ P10+ P11+ P12+ P13+ P14+ P15+ P16+ P17+ P18+ P19+ P20+ P21+ P22+ P23+ P24+ P25+ P26+ P27+ P28+ P29+ P30+ P31+ P32+ P33+ P34+ P35+ P36+ P37+ P38+ P39+ P40+ P41+ P42+ P43+ P44+ P45+ P46+ P47+ P48+ P49+ P50+ P51+ P52+ P53+ P54+ P55+ P56+ P57+ P58+ P59+ P60+ P61+ P62+ P63+ P64+ P65+ P66+ P67+ P68+ P69+ P70+ P71+ P72+ P73+ P74+ P75+ P76+ P77+ P78+ P79+ P80+ P81+ P82+ P83+ P84+ P85+ P86+ P87+ P88+ P89+ P90+ P91+ P92+ P93+ P94+ P95+ P96+ P97+ P98+ P99+ P100+ P101+ P102+ P103+ P104+ P105+ P106+ P107+ P108+ P109+ P110+ P111+ P112+ P113+ P114+ P115+ P116+ P117+ P118+ P119+ P120+ P121+ P122+ P123+ P124+ P125+ P126+ P127+ P128+ P129+ P130+ P131+ P132+ P133+ P134+ P135+ P136+ P137+ P138+ P139+ P140+ P141+ P142+ P143+ P144+ P145+ P146+ P147+ P148+ P149+ P150+ P151+ P152+ P153+ P154+ P155+ P156+ P157+ P158+ P159+ P160+ P161+ P162+ P163+ P164+ P165+ P166+ P167+ P168+ P169+ P170+ P171+ P172+ P173+ P174+ P175+ P176+ P177+ P178+ P179+ P180+ P181+ P182+ P183+ P184+ P185+ P186+ P187+ P188+ P189+ P190+ P191+ P192+ P193+ P194+ P195+ P196+ P197+ P198+ P199+ P200+ P201+ P202+ P203+ P204+ P205+ P206+ P207+ P208+ P209+ P210+ P211+ P212+ P213+ P214+ P215+ P216+ P217+ P218+ P219+ P220+ P221+ P222+ P223+ P224+ P225+ P226+ P227+ P228+ P229+ P230+ P231+ P232+ P233+ P234+ P235+ P236+ P237+ P238+ P239+ P240+ P241+ P242+ P243+ P244+ P245+ P246+ P247+ P248+ P249+ P250+ P251+ P252+ P253+ P254+ P255+ P256+ P257+ P258+ P259+ P260+ P261+ P262+ P263+ P264+ P265+ P266+ P267+ P268+ P269+ P270+ P271+ P272+ P273+ P274+ P275+ P276+ P277+ P278+ P279+ P280+ P281+ P282+ P283+ P284+ P285+ P286+ P287+ P288+ P289+ P290+ P291+ P292+ P293+ P294+ P295+ P296+ P297+ P298+ P299+ P300+ P301+ P302+ P303+ P304+ P305+ P306+ P307+ P308+ P309+ P310+ P311+ P312+ P313+ P314+ P315+ P316+ P317+ P318+ P319+ P320+ P321+ P322+ P323+ P324+ P325+ P326+ P327+ P328+ P329+ P330+ P331+ P332+ P333+ P334+ P335+ P336+ P337+ P338+ P339+ P340+ P341+ P342+ P343+ P344+ P345+ P346+ P347+ P348+ P349+ P350+ P351+ P352+ P353+ P354+ P355+ P356+ P357+ P358+ P359+ P360+ P361+ P362+ P363+ P364+ P365+ P366+ P367+ P368+ P369+ P370+ P371+ P372+ P373+ P374+ P375+ P376+ P377+ P378+ P379+ P380+ P381+ P382+ P383+ P384+ P385+ P386+ P387+ P388+ P389+ P390+ P391+ P392+ P393+ P394+ P395+ P396+ P397+ P398+ P399+ P400+ P401+ P402+ P403+ P404+ P405+ P406+ P407+ P408+ P409+ P410+ P411+ P412+ P413+ P414+ P415+ P416+ P417+ P418+ P419+ P420+ P421+ P422+ P423+ P424+ P425+ P426+ P427+ P428+ P429+ P430+ P431+ P432+ P433+ P434+ P435+ P436+ P437+ P438+ P439+ P440+ P441+ P442+ P443+ P444+ P445+ P446+ P447+ P448+ P449+ P450+ P451+ P452+ P453+ P454+ P455+ P456+ P457+ P458+ P459+ P460+ P461+ P462+ P463+ P464+ P465+ P466+ P467+ P468+ P469eng (t) = [a Load(t) + b RPM(t) + g] K T K H Obtain the budget working condition of the load motor.

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

[0077] Wherein, Load represents the real-time load signal, RPM represents the motor speed, a, b represent the weight coefficients of the real-time load signal and the motor speed, g represents the bias constant, K T , K H respectively represent the temperature correction coefficient and the altitude correction coefficient, m represents the total mass of the vehicle, g represents the gravity acceleration, μ represents the rolling resistance coefficient, θ represents the road slope, v represents the vehicle speed, p, C d , A respectively represent the air density, the wind resistance coefficient and the windward area.

[0078] The real-time load signal can be directly obtained through the accelerator pedal opening or the hydraulic system pressure signal, such as collecting pedal position sensor, hydraulic pump pressure sensor and other signals through vehicle CAN bus, which reflects the driver's torque demand for the engine, for example, the opening increases when accelerating, and the load increases; The load decreases when braking or idling. The motor speed is the number of revolutions per minute of the motor, unit r / min, which can be monitored in real time through crankshaft position sensor or flywheel speed sensor, which represents the dynamic working frequency of the engine, directly affecting the power output efficiency and fuel consumption. The weight coefficients of the real-time load signal and the motor speed can be calibrated by historical data, such as based on experimental data (such as bench test or road test), using multiple linear regression or least squares method to fit the optimal value, etc. The bias constant is used to compensate for unmodeled static power loss (such as mechanical friction, accessory power consumption), which can be measured by experiment under engine no-load, idle condition.

[0079] Temperature correction coefficient K T = 1 - l (T env - T base ), wherein T env , T base respectively represent the real-time environment temperature and the reference environment temperature (usually 25 degrees Celsius), and l represents the temperature attenuation coefficient, which can be set in the range of 0.005-0.015 / ℃. Altitude correction coefficient K H = 1 - k (H / 1000), H represents the altitude, and k represents the altitude attenuation coefficient, which can be set in the range of 0.08-0.12.

[0080] The increase of ambient temperature will cause the decrease of motor power, and high temperature will cause the decrease of heat dissipation efficiency, affecting the thermal efficiency. The increase of altitude will cause the decrease of air density, and then cause the power attenuation. According to the formula P eng (t)=[α·Load(t)+β·RPM(t)+γ]·K T ·K H The budget working state of the load motor is obtained by considering temperature and altitude, and the product correction instead of superposition correction is adopted, which is more consistent with the actual nonlinear effect. For real-time ambient temperature and altitude, the real-time parameters can be obtained by the vehicle-mounted temperature sensor and air pressure sensor, and updated every 10 seconds.

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

[0082] For the road conditions in front, the front road conditions (slope and speed) can be obtained by the vehicle-mounted sensors (such as camera, GPS), and the budget working condition of the current road is calculated. The rolling resistance coefficient is dimensionless, which can be understood as the friction coefficient between tire and road surface, and the air resistance coefficient is dimensionless. The windward area of the vehicle is the projection area of the vehicle perpendicular to the driving direction.

[0083] respectively represent the slope and rolling resistance term and the aerodynamic resistance term. sinθ represents the gravity component caused by slope, and the vehicle needs to overcome gravity when climbing uphill, and energy can be recovered when descending. μcosθ represents the friction loss between tire and road surface, which is proportional to vehicle speed. v 3 v indicates that the influence of air resistance on energy demand increases significantly when driving at high speed. For the rolling resistance coefficient and the air resistance coefficient, they can be calibrated by historical data to improve the prediction accuracy.

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

[0085] S221, constructing an SOC change rate equation

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

[0087] Where Q represents the rated capacity of the power battery, η ch η dis P represents the charging efficiency and discharging efficiency, respectively. charge (t) represents the regenerative braking feedback power. This represents the optimal estimate of SOC at the current time t. Based on the optimal estimate at time t-1, the prior prediction of SOC at time t is K. t Indicates Kalman gain, SOC meas,t This 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 of the battery voltage / current sensor. The optimal SOC estimate at the current time t can be understood as the SOC correction result after fusing the predicted value and the measured value, which has the smallest mean square error.

[0089] For the Kalman gain Among them, P k|K-1 R k These 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 OCV represents the open-circuit voltage of the power battery. The state vector retains only three core state variables: SOC, OCV, and polarization voltage, which reduces the computational load compared to the traditional EKF (which typically includes 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 slope, and battery voltage, which improves prediction robustness. The SOC rate of change equation and Kalman filter retain only the core state variables (SOC and voltage), reducing computational complexity. In other words, this embodiment significantly reduces computational complexity while ensuring prediction accuracy, making it suitable for the complex operating conditions of commercial vehicles.

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

[0092] S3, Obtain the real-time charge of the supercapacitor;

[0093] S4. If the real-time power is greater than a first preset multiple of the rated capacity of the supercapacitor, then the power battery is charged through the supercapacitor to reduce the real-time power to a standard preset multiple of the rated capacity of the supercapacitor.

[0094] S5. If the real-time power is less than a second preset multiple of the rated capacity of the supercapacitor, the supercapacitor is charged through the power battery to increase the real-time power to a standard preset multiple of the rated capacity of the supercapacitor.

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

[0096] For supercapacitors to achieve capacitance compensation, they must be in an adjustable state. To enable them to increase or decrease the battery's charge, they must maintain a moderate charge level—around 0.5. The VCU (Vehicle Control Unit) monitors the supercapacitor's charge. When the charge is greater than 0.55, the supercapacitor charges the battery, reducing the charge to 0.5. When the charge is less than 0.45, the battery charges the supercapacitor, increasing its charge to 0.5.

[0097] Thus, by setting the first preset multiple, the standard preset multiple, and the second preset multiple, the adjustment function of the supercapacitor can be better realized.

[0098] In one embodiment, such as Figure 7 As shown, 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:

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

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

[0101] S8, 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.

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

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

[0104] The specific upper and lower limits of the first, second and third state intervals, the first, second and third power intervals can be set and adjusted according to specific conditions, which will not be described here.

[0105] By dividing the output power of the fuel cell into high, medium and low power intervals 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 prolonged.

[0106] An embodiment of the present application also provides a fuel cell commercial vehicle power optimization system based on a super capacitor, which is used to realize the fuel cell commercial vehicle power optimization method. Figure 8 As shown in the figure, it comprises a power adjustment module and an electric quantity 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 to adjust the power output of the fuel cell in different SOC states according to the SOC state of the power battery; the electric quantity exchange module is used to predict the SOC fluctuation state of the power battery, and to adjust the energy exchange between the power battery and the super capacitor with the goal of minimizing the number of fuel cell output power fluctuations.

[0108] Specifically, the regulation of the super capacitor is based on global optimization, and the VCU adopts an optimal control principle (such as dynamic programming, genetic algorithm) to optimize the control strategy, thereby reducing the switching frequency of the fuel cell power interval in a fluctuating driving environment. By precisely controlling the power regulation and regulation time of the super capacitor on the power battery, the intelligent regulation of the super capacitor is exerted, thereby reducing the fluctuation of vehicle power distribution.

[0109] For the regulation time, it can be understood as a variable time interval value ΔT2 based on global optimization. For example, assuming that the current time is T0, if the SOC fluctuation state of the power battery is predicted, the power battery power is lower than the low critical value 40% or lower 30% and the like within the future time T0+ΔT2, the power battery is compensated by the super capacitor. The critical difference here refers to the difference between the high critical value and the low critical value, which is used to ensure the flexibility of power regulation and avoid excessive frequent charging and discharging.

[0110] The time interval value ΔT2 can be adjusted according to the actual situation, such as being remotely set by the technician according to experience, or being adjusted according to the road conditions, such as appropriately increasing the time interval value in flat road conditions, or appropriately reducing the time interval value in curved roads, inclined road surfaces with a slope greater than a preset slope value, or congested roads, so as to reduce the fluctuation frequency of the fuel cell output power as much as possible and reduce the switching frequency. In this way, by adjusting the energy exchange between the power battery and the super capacitor with the goal of minimizing the fluctuation frequency of the fuel cell output power, the frequent power changes of the fuel cell can be reduced, and the service life of the fuel cell can be prolonged.

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

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

[0115] The fuel cell commercial vehicle power optimization system 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 power output fluctuations of the fuel cell, which can avoid the instability of fuel cell power output caused by SOC fluctuations near the critical value, thereby reducing the frequent power changes of the fuel cell and extending its service life.

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

[0117] The fuel cell and the power battery work together to power the load motor, employing a combination of a high-power fuel cell and a low-power power battery. The high-power fuel cell directly supplies power to the inverter, which then powers the load motor. The low-power power battery first meets the voltage requirements through a DC / DC converter before supplying power to the load motor through the inverter. The DC / DC converter is responsible for energy transfer and regulation between the different power systems.

[0118] Supercapacitors possess both low energy density and high power density, enabling them to release a large amount of energy in a short time. Their primary function is to regulate the state of charge (SOC) of the power battery, without contributing to the vehicle's power output. Supercapacitors are controlled by a VCU controller to adjust the SOC of the power battery to optimize overall system performance.

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

[0120] The system determines the adjustment and compensation power signal in real time through the VCU controller, and dynamically adjusts the energy exchange between the super capacitor 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 condition. When the SOC approaches the critical value, the VCU enters the pre-adjustment and compensation state, and judges whether the SOC of the battery needs to be adjusted in combination with the power condition of the super capacitor, so as to ensure the stable output of the fuel cell.

[0121] The fuel cell commercial vehicle power optimization system collects the output data of the fuel cell, the power battery and the super capacitor in real time by simulating different driving conditions, analyzes the performance and performance of the system under various conditions, so as to optimize the system design.

[0122] As shown in Figure 10 The fuel cell, the power battery, the load motor, the inverter and the DC / DC converter are used as the power driving module. In the power driving module, the fuel cell and the power battery are used as the power source to drive the load motor to drive the whole vehicle. The load motor receives the actual power from the fuel cell and the power battery, and outputs the power demand in comparison with the simulation condition input. The high-power fuel cell can provide high and stable voltage to meet the needs of the inverter and the motor, and the small-power power battery needs to be boosted by the DC / DC converter to meet the voltage demand. The inverter is distributed between the battery and the motor, and the inverter is responsible for converting the direct current output by the battery into 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, the output power distribution of the fuel cell and the power battery is mainly adjusted according to the remaining power state SOC of the power battery. The VCU controller is the core of this module, and the VCU extracts the SOC of the power battery adopted by the BMS and combines the power demand feedback signal to realize relatively complete power distribution.

[0124] The super capacitor, the DC / DC converter and the VCU controller are used as the capacitor adjustment and compensation control module. The capacitor adjustment and compensation control is optimized on the basis of the SOC control strategy, and is a solution to the multiple jumps of the working power range of the fuel cell under the fluctuating SOC state of the multiple fluctuating road conditions.

[0125] VCU controller as the core of the process, VCU controller receives the budget work state from the load motor and the budget working condition from the analog working condition input, combined with the vehicle parameters, calculate the power battery power consumption state to get the SOC fluctuation state of power battery. Combined with the SOC fluctuation state and the high and low limit value of SOC in the SOC control strategy, predict whether the working interval of the fuel cell will be in the fluctuation state, combined with the predicted SOC amount, super capacitor power value input to adjust the power signal to the super capacitor.

[0126] The super capacitor receives the power adjustment signal, exchanges power between the DC / DC converter and the power battery, so that the SOC of the power battery is in a relatively stable interval, reducing the switching of the fuel cell working power interval.

[0127] The power optimization system also includes an adjustment module. For the adjustment module, it is mainly used to make the super capacitor in a preparation state, that is, the capacitance power level of the super capacitor is 0.5 (i.e. 50%).

[0128] Specifically, for the super capacitor, if you want to achieve the function of capacitance adjustment and compensation, the super capacitor must be in a state of adjustment and compensation, and the super capacitor must have the function of increasing the power of the power battery and reducing the power of the power battery, that is, it must maintain a medium power state - the super capacitor power is 0.5.

[0129] When the super capacitor power is high (for example, greater than 0.5), its main function is to provide power for the power battery and reduce the power loss of the power battery. When the power is low (for example, less than 0.45), the super capacitor will receive the power of the power battery to maintain its power within a reasonable range for subsequent adjustment and use. In order to optimize power distribution and prolong the service life of the system, the power state of the super capacitor is usually kept at about 0.5, that is, the power is in a medium charge 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 super capacitor through the VCU controller. When the power of the super capacitor is greater than 0.55, the super capacitor charges the power battery, reducing the power of the super capacitor to 0.5; when the power of the super capacitor is less than 0.45, the power battery charges the super capacitor, increasing the power of the super capacitor to 0.5.

[0131] Among them, such as Figure 11As shown, the power exchange module is as a decision module, and has a higher priority than the adjustment module. The thought of the power exchange module is to firstly combine the road working condition and the vehicle running working condition, to predictively give the fluctuation condition of the power battery SOC, to judge whether the SOC fluctuation exceeds the SOC limit value, if the SOC fluctuation exceeds the limit value, to judge whether the electric quantity contained in the super capacitor can adjust and compensate the overflow value of the power battery SOC, if yes, to perform the adjustment and compensation of the super capacitor. The selection of ΔT1 and ΔT2 is based on the global optimization, and the time period is determined based on the target of minimizing the switching times of the fuel cell working power interval. T0 is the initial time point when the statistics is started, and ΔT1 is the time increment after T0.

[0132] The technical features of the above-described embodiments can be combined in any manner. To make the description concise, all possible combinations of the technical features in the above-described embodiments are not described, but as long as the combinations of the technical features do not contradict each other, they should be considered within the scope of the present disclosure.

[0133] The above-described embodiments only express several implementation manners of the present application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that, for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for fuel cell commercial vehicle power optimization based on supercapacitor, characterized in that, The fuel cell commercial vehicle power optimization method comprises 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 in different SOC states is adjusted according to the SOC state of the power battery; The SOC fluctuation state of the power battery is predicted, and the energy exchange between the power battery and the super capacitor is adjusted to minimize the number of fuel cell output power fluctuations; The SOC fluctuation state of the power battery comprises the following steps: The budget working state of the load motor and the budget working condition of the current road are obtained; The SOC fluctuation state of the power battery is predicted according to the budget working state and the budget working condition; The energy exchange between the power battery and the super capacitor comprises the following steps: According to the SOC fluctuation state of the power battery, it is predicted whether the power of the power battery is higher than a first critical value, if yes, it is judged whether the power of the super capacitor is greater than the critical difference value of the power battery, if yes, the super capacitor is charged by the power battery; According to the SOC fluctuation state of the power battery, it is predicted whether the power of the power battery is lower than a second critical value, if yes, it is judged whether the power of the super capacitor is greater than the critical difference value of the power battery, if yes, the power battery is charged by the super capacitor; The first critical value is greater than the second critical value; The specific method for obtaining the budget working state of the load motor and the budget working condition of the current road comprises the following steps: According to the formula Obtaining a budget operating state of the load motor; According to the formula Obtaining a budgetary condition of the current road; wherein, represents a real-time load signal, represents a motor rotation speed, represents a weight coefficient of the real-time load signal and the motor rotation speed, represents a bias constant, respectively represent a temperature correction coefficient and an altitude correction coefficient, represents a total mass of the vehicle, represents a gravitational acceleration, represents a rolling resistance coefficient, represents a road slope, represents a vehicle speed, respectively represent an air density, a wind resistance coefficient, and a windward area; The specific method for predicting the SOC fluctuation state of the power battery according to the budget working state and the budget working condition comprises the following steps: Building the SOC change rate equation ; By kalman filter Real-time correction of SOC prediction error; in, Indicates the rated capacity of the power battery. These represent charging efficiency and discharging efficiency, respectively. Indicates regenerative braking feedback power. Indicates the current time The optimal estimate of SOC, At any moment Based on the optimal estimate of time The SOC prior prediction value, Indicates Kalman gain, Indicates the current time The actual measured SOC value.

2. The ultracap-based fuel cell commercial vehicle power optimization method of claim 1 wherein, The fuel cell commercial vehicle power optimization method further comprises the following steps: The real-time power of the super capacitor is obtained; If the real-time power is greater than the first preset multiple of the rated capacity of the super capacitor, the power battery is charged by the super capacitor, so that the real-time power is reduced to the standard preset multiple of the rated capacity of the super capacitor; If the real-time power is less than the second preset multiple of the rated capacity of the super capacitor, the super capacitor is charged by the power battery, so that the real-time power is increased to the standard preset multiple of the rated capacity of the super capacitor; The first preset multiple> standard preset multiple> second preset multiple, and the first preset multiple and the second preset multiple are both in the range of (0, 1).

3. The ultracap-based fuel cell commercial vehicle power optimization method of claim 2 wherein, 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 comprises the following steps: When the SOC state of the power battery is in a first state interval, the power output of the fuel cell is adjusted to a first power interval; When the SOC state of the power battery is in a second state interval, the power output of the fuel cell is adjusted to a second power interval; When the SOC state of the power battery is in a third state interval, the power output of the fuel cell is adjusted to a third power interval; 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.

4. A supercapacitor-based fuel cell commercial vehicle power optimization system for implementing the fuel cell commercial vehicle power optimization method according to any one of claims 1-3, characterized in that, Comprise: The power adjustment module is used for jointly supplying power to the load motor by the fuel cell and the power battery, and adjusting the power output of the fuel cell under different SOC states according to the SOC state of the power battery; The power exchange module is used for predicting the SOC fluctuation state of the power battery, and adjusting the energy exchange between the power battery and the super capacitor to minimize the output power fluctuation frequency of the fuel cell.

5. The ultracapacitor-based fuel cell commercial vehicle power optimization system of claim 4, wherein, The power exchange module comprises: A prediction unit is used for obtaining the budget working state of the load motor and the budget working condition of the current road; An SOC acquisition unit is used for predicting the SOC fluctuation state of the power battery according to the budget working state and the budget working condition.

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