Adaptive Optimization Thermal Management Control Method, System and Thermal Management System for Liquid-Cooled Power Source

Abstract

The present invention provides an adaptive optimization thermal management control method, system and thermal management system for a liquid-cooled power source, realizing high-performance temperature control under varying working conditions and ensuring the efficient and stable operation of the power source. The time-delay estimation module and the state predictor module accurately estimate the system time delay and the real-time delay-free state inside the system, compensating for performance decays such as temperature overshoot and slow response; aiming at the measurement and estimation problems of the heat generation of the power source and the heat dissipation of the radiator under varying working conditions, the disturbance estimator measures the coolant temperature information at the outlets of the power source and the radiator to accurately estimate the uncertain heat exchange amount of the system, saving costs, and aiming at the problems of energy consumption optimization and internal temperature consistency of the thermal management system; the equilibrium point optimization module calculates the working point of the radiator outlet temperature corresponding to the optimal energy consumption of the system on the premise of meeting the temperature consistency requirement; aiming at the high-performance temperature tracking control requirement, the state tracking control module can achieve fast-response and high-precision temperature control.

Description

Technical Field

[0001] The present invention belongs to the technical field of thermal management control of vehicle power sources, and relates to thermal management control strategies for new energy vehicle power batteries, engines, and proton exchange membrane fuel cells, and specifically to an adaptive optimization thermal management control method and system for liquid-cooled power sources and a thermal management system. Background Art

[0002] Engines, power batteries, and proton exchange membrane fuel cells are the core power sources of new energy vehicles. Their working efficiency, stability, service life and other performance are greatly affected by temperature. Therefore, an efficient thermal management system control strategy is required to control the temperature of the power source within the expected temperature range and meet the internal temperature consistency requirements of the power source.

[0003] Due to the complex and changeable working environment of the vehicle, there are many uncertain heat exchange quantities in the thermal management system, which are difficult to accurately model, bringing challenges to the design of the control strategy. The pipe connection characteristics in the thermal management system bring about a large time delay, which makes the temperature control performance worse. In addition, for high-power power sources, reducing the energy consumption of the thermal management system can effectively improve the energy efficiency of the vehicle while meeting the temperature control performance.

[0004] In the face of the control requirements and control difficulties of the above thermal management system, the current control strategy is basically to improve the design structure of the thermal management system and design a rule-based control method based on engineering experience and a large number of experimental debugging. Faced with complex and changeable working conditions, the above methods have poor adaptability and interference suppression capabilities, and it is difficult to maintain high-precision temperature control. In addition, the above methods do not consider the energy consumption optimization of the thermal management system and cannot improve the energy efficiency of the system. Summary of the invention

[0005] In response to the above technical problems, the present invention provides an adaptive optimization thermal management control method for a liquid-cooled power source, which achieves high-performance temperature control under changing working conditions and ensures efficient and stable operation of the power source.

[0006] The purpose of the present invention is achieved through the following technical solutions:

[0007] An adaptive optimization thermal management control method for a liquid-cooled power source comprises the following steps:

[0008] 1. Use the sampling module to obtain the heat source outlet temperature and the radiator outlet temperature in the thermal management system, and the sampling module outputs the power source temperature information;

[0009] At the same time, the electric water pump control quantity is input to the delay estimator, and the delay estimator outputs the estimated system time delay. The calculation formula of the system time delay is:

[0010] τ=γ 4u 1 +γ 5 (3);

[0011] Among them, γ 4 and γ 5 is the system attribute parameter, u 1 It is the control quantity of the electric water pump;

[0012] 2. Input the air temperature, power source temperature information, and the thermal management system actuator time delay control signal output by the second data stack module into the interference estimator, and the interference estimator outputs the estimated value of the uncertain parameters in the operation of the thermal management system; the calculation formula of the estimated value of the uncertain parameters is:

[0013]

[0014] in

[0015] Formula (6) where

[0016] Formula (5) where

[0017] Among them, x 1 is the heat source outlet temperature, x 2 is the radiator outlet temperature, u 1 is the control quantity of the electronic water pump, u 2 is the control quantity of the electronic thermostat, u 3 is the control quantity of the electronic fan, ζ 1 is the heat transferred from the heat source to the coolant, 2 is the estimated error of the heat dissipation of the radiator, ζ i , i∈[1,2] is the unknown parameter of the thermal management system, γ i ,i∈[1,3] is the system attribute parameter; κ 1 are the parameters to be designed, is the estimated value of ζ, Π is the positive definite matrix to be designed; x i,τ It represents the state value of the system after a pure time delay, x i (t-τ) is the time-delayed temperature information of the power source output by the sampling module;

[0018] 3. The estimated value of the uncertain parameter of the thermal management system output by the interference estimator is input to the first data stack module for storage. The first data stack module outputs the estimated value of the uncertain parameter of the thermal management system stored internally. Then, the estimated value of the uncertain parameter with time delay output by the first data stack is input to the system estimator. The thermal management system actuator control signal and the power source temperature information stored in the third data stack module are input to the system estimator. The system estimator outputs the estimated value of the state variable without time delay. The calculation formula of the estimated value of the state variable without time delay is as follows:

[0019]

[0020]

[0021]

[0022]

[0023] in, is the state variable of the system without time delay.

[0024] At the same time, the estimated value of the uncertain parameters output by the interference estimator module, the expected value of the heat source outlet temperature, the lower limit setting value of the expected radiator outlet temperature and the air temperature are input into the balance point optimization module, and the balance point optimization module outputs the optimal setting value of the radiator outlet temperature; the calculation formula of the optimal setting value of the radiator outlet temperature is:

[0025] min J op (x 2d ) = f 1 (u 1 (x 2d ))+f 2 (u 1 (x 2d ))

[0026] st

[0027]

[0028]

[0029]

[0030]

[0031] Among them, the function f 1 is a known electronic water pump power function, function f 2 is the known power function of the electronic fan; S max They are x 2d The maximum setting value of the acceptable range; It is the lower limit of the value range of the electronic water pump control quantity; It is the upper limit of the range of the electronic water pump control quantity; It is the lower limit of the range of electronic fan control value; is the upper limit of the electronic fan control value range; x 1d is the expected value of the heat source outlet temperature, x 2d is the expected value at the radiator outlet;

[0032] 4. The estimated value of the uncertain parameter output by the interference estimator, the estimated value of the time-delayed state variable output by the system estimator, the optimal setting value of the radiator outlet temperature output by the equilibrium point optimization module, the expected value of the heat source outlet temperature and the air temperature are input into the state tracking controller, and the output signal of the state tracking controller is the control signal of the thermal management system actuator; the calculation formula of the control signal of the thermal management system actuator is:

[0033]

[0034] Among them, k 1 , k 2 , k 3 and k 4 is the control parameter to be designed;

[0035] Inputting the actuator control signal output by the state tracking controller into the sub-controller of the relevant actuator in the thermal management system;

[0036] At the same time, the actuator control signal output by the state tracking controller is input into the second data stack module and the third data stack module for storage. The output of the second data stack module stores the thermal management system actuator time delay control signal internally, and the output of the third data stack stores the thermal management system actuator control signal internally.

[0037] The present invention also provides an adaptive optimization thermal management control system based on a liquid cooling power source, comprising 7 submodules, namely:

[0038] Thermal management system model module, used to establish a thermal management system model to simulate the operating conditions of the thermal management system during engine operation and output the state variables of the system;

[0039] A delay estimator module is used to estimate the pure time delay of the system, the input signal of the delay estimator module is the control quantity of the electric water pump, and the output signal is the estimated pure time delay of the system;

[0040] A data stack module is used to store the most recent continuous input signals. The input signals of the data stack module are the control variables and state variables to be stored, and the output signals are the internally stored variables.

[0041] A sampling module is used to collect the temperature at the heat source and the heat sink outlet, the sampling module input signal is the first temperature sensor and the second temperature sensor, and the output signal is the power source temperature information;

[0042] An interference estimator module is used to estimate uncertain parameters in system operation. The input signals of the interference estimator are air temperature, temperature information and time delay control quantity information output by the first data stack of the state tracking controller. The output signal is an estimated value of the uncertain parameter.

[0043] The state estimator module is used to estimate the time-delay state variables of the system and compensate for the performance degradation of the system due to time delay; the state estimator module is composed of the second data stack of the state tracking controller and the system estimator module, the input signal of the second data stack of the state tracking controller is the actuator control quantity signal output by the state tracking controller, and the output signal is the actuator control quantity signal stored internally; the input signal of the system estimator module is the actuator control quantity stored internally output by the second data stack of the state tracking controller, the estimated value of the uncertain parameters output by the interference estimator data stack and the temperature information, and the output signal is the estimated value of the time-delay state variables;

[0044] The balance point optimization module is used to calculate the optimal setting value of the radiator outlet temperature corresponding to the optimal energy consumption of the system; the input signal of the balance point optimization module is the expected value of the heat source outlet temperature, the lower limit setting value of the expected radiator outlet temperature, the air temperature, and the estimated value of the uncertain parameters output by the interference estimator module, and the output signal is the optimal setting value of the radiator outlet temperature.

[0045] The state tracking controller module is used to calculate the control signals of the electronic water pump, electronic fan and electronic thermostat; the input signals of the state tracking controller are the air temperature, the expected value of the heat source outlet temperature, the optimal setting value of the radiator outlet temperature, the uncertain parameter estimation value output by the interference estimator module and the delay-free state variable estimation value output by the state estimator module, and the output signal is the control signal of the thermal management system actuator (electronic water pump, electronic fan, electronic thermostat).

[0046] The present invention also provides a thermal management system, including a heat source heating circuit and a heat source heat dissipation circuit, the heat source heating circuit includes a heat source, an electronic thermostat, an electric water pump, and a first temperature sensor; the heat source heat dissipation circuit includes a heat source, an electronic thermostat, a radiator, an electric water pump, and a second temperature sensor; the outlet end of the water jacket inside the heat source is connected to the inlet of the first temperature sensor, and the outlet of the first temperature sensor is connected to the inlet of the electronic thermostat; the outlet 1 of the electronic thermostat is connected to the inlet 1 of the three-way valve; the outlet 2 of the electronic thermostat is connected to the inlet of the radiator; the outlet of the radiator is connected to the inlet of the second temperature sensor; the outlet of the second temperature sensor is connected to the inlet 2 of the three-way valve; the outlet of the three-way valve is connected to the inlet of the electric water pump; the outlet of the electric water pump is connected to the inlet of the water jacket inside the heat source, the input port of the control system 8 is respectively connected to the first temperature sensor and the second temperature sensor; the output port is respectively connected to the electronic thermostat sub-controller, the electric water pump sub-controller, and the radiator sub-controller, and the control system 8 directly sends control instructions to the sub-controllers of the relevant actuators.

[0047] The adaptive optimization thermal management control method provided by the present invention is aimed at the thermal management system of the power source (engine, power battery, fuel cell) based on liquid cooling, and its control strategy includes 5 core modules, namely, delay estimation module, interference estimator module, balance point optimization module, state predictor module and state tracking control module. In view of the delay problem caused by the coolant transmission and actuator action of the liquid cooling system, the delay estimation module and the state predictor module can accurately estimate the system delay and the real-time delay-free state inside the system, thereby compensating for the performance degradation such as temperature overshoot and slow response caused by the delay problem. In view of the measurement and estimation problem of the heat generation of the power source and the heat dissipation of the radiator under changing working conditions, the interference estimator module only needs to measure the coolant temperature information of the power source and the radiator outlet to accurately estimate the uncertain heat exchange amount of the system, avoiding the configuration of more complex sensors and saving system costs. In view of the energy consumption optimization problem and the internal temperature consistency problem of the thermal management system, the balance point optimization module can calculate the radiator outlet temperature working point corresponding to the optimal energy consumption of the system under the premise of meeting the temperature consistency requirements. In view of the high-performance temperature tracking control requirements, the state tracking control module can achieve fast response and high-precision temperature control.

[0048] The control method described in the present invention can achieve high-precision and fast-response temperature tracking control on the premise of meeting the temperature consistency requirements within the system, thereby ensuring efficient and stable operation of the power source; the control system has high adaptability and strong anti-interference characteristics for changing working conditions and large time delay problems; and it performs optimal power allocation for the actuator to achieve optimal energy consumption of the thermal management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of a thermal management system applicable to the present invention;

[0050] Figure 1 In: 1. First temperature sensor, 2. Heat source, 3. Electric water pump, 4. Electronic thermostat, 5. Three-way valve, 6. Radiator (integrated fan), 7. Second temperature sensor, 8. Controller, 9. Pipeline mechanical connection, 10. Controller input connection, 11. Controller output connection.

[0051] Figure 2 A control block diagram of one embodiment of the present invention;

[0052] Figure 2 In: A, interference estimator, B, balance point optimization module, C, first data stack module, D, state tracking controller, E, second data stack module, F, thermal management system, G, third data stack module, H, system estimator, M, state estimator module, J, sampling module, K, delay estimator.

[0053] Figure 3 Schematic diagram of the experimental platform of the embodiment.

[0054] Figure 4 Working condition 1 of the embodiment.

[0055] Figure 5 Temperature variation curve of working condition 1 of the embodiment.

[0056] Figure 6 Working condition 1 temperature error variation curve of the embodiment.

[0057] Figure 7 Working condition of the embodiment - water pump regulation curve.

[0058] Figure 8 Working condition of the embodiment - fan adjustment curve.

[0059] Fig. 9 Working condition 2 of the embodiment.

[0060] Fig.10 Temperature variation curve of working condition 2 of the embodiment.

[0061] Fig.11 Temperature error variation curve of working condition 2 of the embodiment.

[0062] Fig.12 The water pump regulation curve of working condition 2 of the embodiment.

[0063] Fig.13 Fan adjustment curve for working condition 2 of the embodiment. DETAILED DESCRIPTION

[0064] To further illustrate the technical content and structural features of the present invention, an embodiment is given below and described in detail with reference to the accompanying drawings. In addition, to highlight the effectiveness of the present invention, an engine is used as an example of a power source to conduct a bench test of a thermal management system, and the experimental results fully demonstrate the high performance of the control strategy. The scope of protection of the present invention is not limited to the following.

[0065] like Figure 1 As shown, the present invention provides an adaptive optimization thermal management control system based on a liquid-cooled power source, including 7 submodules, namely: a thermal management system model module, which is used to establish a thermal management system model to simulate the operating conditions of the thermal management system during the operation of the engine and output the state variables of the system; a delay estimator module, which is used to estimate the pure time delay of the system, the input signal of the delay estimator module is the control quantity of the electric water pump, and the output signal is the estimated pure time delay of the system; a data stack module, which is used to store the most recent continuous input signals, the input signal of the data stack module is the control variable and state variable to be stored, and the output signal is the internally stored variable; a sampling module, which is used to collect the temperature at the outlet of the heat source and the radiator, the input signal of the sampling module is the first temperature sensor and the second temperature sensor, and the output signal is the power source temperature information; an interference estimator module, which is used to estimate the uncertain parameters in the operation of the system, the input signal of the interference estimator is the air temperature, temperature information and the time delay control quantity information output by the first data stack of the state tracking controller, and the output signal is the estimated value of the uncertain parameter; a state predictor module, which is used to estimate the delay-free state variables of the system and compensate for the performance degradation of the system due to time delay; the state predictor module is composed of a state tracking controller The state tracking controller is composed of a second data stack and a system estimator module. The input signal of the second data stack of the state tracking controller is the actuator control quantity signal output by the state tracking controller, and the output signal is the actuator control quantity signal stored internally. The input signal of the system estimator module is the actuator control quantity stored internally output by the second data stack of the state tracking controller, the estimated value of the uncertain parameters and the temperature information output by the interference estimator data stack, and the output signal is the estimated value of the state variable without delay. The balance point optimization module is used to calculate the optimal setting value of the radiator outlet temperature corresponding to the optimal energy consumption of the system. The input signal of the balance point optimization module is the heat source outlet. The expected temperature value, the lower limit setting value of the expected radiator outlet temperature, the air temperature, the estimated value of the uncertain parameters output by the interference estimator module, and the output signal is the optimal setting value of the radiator outlet temperature; the state tracking controller module is used to calculate the control signals of the electronic water pump, the electronic fan, and the electronic thermostat; the input signals of the state tracking controller are the air temperature, the expected value of the heat source outlet temperature, the optimal setting value of the radiator outlet temperature, the estimated value of the uncertain parameters output by the interference estimator module, and the estimated value of the delay-free state variable output by the state estimator module, and the output signal is the control signal of the thermal management system actuator (electronic water pump, electronic fan, electronic thermostat).

[0066] like Figure 2 As shown, the present invention provides a thermal management control method based on the above control system, comprising the following steps:

[0067] 1. Use the sampling module to obtain the heat source outlet temperature and the radiator outlet temperature in the thermal management system, and the sampling module outputs the power source temperature information; at the same time, the electric water pump control quantity is input to the delay estimator, and the delay estimator outputs the estimated system time delay;

[0068] 2. Inputting the air temperature, the power source temperature information, and the thermal management system actuator time delay control signal output by the second data stack module into the interference estimator, and the interference estimator outputs the estimated value of the uncertain parameters in the operation of the thermal management system;

[0069] 3. Input the estimated value of the uncertain parameter of the thermal management system output by the interference estimator to the first data stack module for storage, the first data stack module outputs the information of the estimated value of the uncertain parameter of the thermal management system stored internally, and then the uncertain parameter estimated value with time delay output by the first data stack, the thermal management system actuator control signal and power source temperature information stored in the third data stack module are input to the system estimator, and the system estimator outputs the estimated value of the state variable without time delay;

[0070] At the same time, the estimated value of the uncertain parameters output by the interference estimator module, the expected value of the heat source outlet temperature, the lower limit setting value of the expected radiator outlet temperature and the air temperature are input into the balance point optimization module, and the output of the balance point optimization module is the optimal setting value of the radiator outlet temperature;

[0071] 4. The uncertain parameter estimation value output by the interference estimator, the delay-free state variable estimation value output by the system estimator, the optimal setting value of the radiator outlet temperature output by the balance point optimization module, the expected value of the heat source outlet temperature and the air temperature are input into the state tracking controller, and the output signal of the state tracking controller is the control signal of the thermal management system actuator; the actuator control signal output by the state tracking controller is input into the sub-controller of the relevant actuator in the thermal management system; at the same time, the actuator control signal output by the state tracking controller is input into the second data stack module and the third data stack module for storage, the output of the second data stack module is the internally stored thermal management system actuator time delay control signal, and the output of the third data stack is the internally stored thermal management system actuator control signal.

[0072] In an embodiment of the present invention, the engine thermal management system is as follows: Figure 1As shown. The engine thermal management system mainly includes two coolant circuits: an engine heating circuit and an engine heat dissipation circuit. Among them, the engine heating circuit includes an engine (heat source) 2, an electronic thermostat 4, an electric water pump 3, and a first temperature sensor 7; the engine (heat source) heat dissipation circuit includes an engine (heat source) 2, an electronic thermostat 4, a radiator 6, an electric water pump 3, and a second temperature sensor 7. In the system, the outlet end of the water jacket inside the heat source is connected to the inlet of the first temperature sensor, and the outlet of the first temperature sensor is connected to the inlet of the electronic thermostat; the outlet 1 of the electronic thermostat is connected to the inlet 1 of the three-way valve; the outlet 2 of the electronic thermostat is connected to the inlet of the radiator; the outlet of the radiator is connected to the inlet of the second temperature sensor; the outlet of the second temperature sensor is connected to the inlet 2 of the three-way valve; the outlet of the three-way valve is connected to the inlet of the electric water pump; the outlet of the electric water pump is connected to the inlet of the water jacket inside the heat source. The input port of the control system 8 is respectively connected to the first temperature sensor and the second temperature sensor; the output port is respectively connected to the electronic thermostat sub-controller, the electric water pump sub-controller, and the radiator sub-controller. The control system 8 directly sends control instructions to the sub-controller of the relevant actuator, and the specific control is completed by the sub-controller of the actuator.

[0073] The control method proposed by the present invention is applicable to the structure and Figure 1 Same or similar thermal management system.

[0074] The design process of the thermal management system control method based on this embodiment is as follows:

[0075] Step 1: Model the following model based on the liquid-cooled power source thermal management system:

[0076]

[0077]

[0078] In formula (1), x 1 is the heat source outlet temperature, x 2 is the radiator outlet temperature, u 1 is the control quantity of the electronic water pump, u 2 is the control quantity of the electronic thermostat, u 3 is the control quantity of the electronic fan, ζ 1 is the heat transferred from the heat source to the coolant, 2 is the estimated error of the heat dissipation of the radiator. Due to the variability of the system operating conditions and the uncertainty of the external environment, ζ i ,i∈[1,2] can be regarded as the unknown parameters of the thermal management system, γ i , i∈[1,3] is the system attribute parameter, which can be obtained through model identification or through the measurement of system structure parameters. The specific expression is as follows:

[0079]

[0080]

[0081]

[0082] In formula (2), c p is the specific heat capacity of the coolant, c a is the specific heat capacity of air, C ec is the heat capacity of the coolant in the water jacket inside the heat source, C rc is the heat capacity of the coolant inside the radiator, θ 1 is the mapping table between the water pump control quantity and the coolant mass flow rate at the water pump outlet in the system, θ 2 It is a mapping table of the fan control quantity and the air mass flow rate at the fan outlet in the system.

[0083] Step 2: Use the delay estimation module to estimate the pure time delay τ of the system. The pure time delay is mainly related to the electronic water pump control quantity u 1 Related, the specific function design is as follows

[0084] τ=γ 4 u 1 +γ 5 (3)

[0085] In formula (3), γ 4 and γ 5 is a parameter that can be obtained through model identification.

[0086] Step 3: Use the data stack module to store the most recently acquired control variables and state variables. The first data stack outputs the estimated value of the uncertain parameter of the time delay The third data stack module outputs the internally stored thermal management system actuator control signal u i (t-θ),θ∈[0,τ], (t-θ),θ∈[0,τ] represents the value range of the output information sequence.

[0087] Step 4: Use the sampling module to collect the temperature information x at the heat source and the heat sink outlet 1 、x 2 .

[0088] Step 5: Use the interference estimator to calculate the estimated values ​​of the unknown parameters of the system. The main steps are as follows:

[0089] (I) The system is redefined as follows:

[0090] x τ = χ(x τ ,u τ )+ξζ

[0091] xτ :=[x 1,τ ,x 2,τ ] T ,x i,τ :=x i (t-τ)

[0092] u τ :=[u 1,τ ,u 2,τ ,u 3,τ ] T ,u i,τ :=u i (t-τ)

[0093]

[0094]

[0095] In formula (3), x i,τ It indicates the state value of the system measured after a pure time delay.

[0096] (ii) Variable x through variable filter τ , χ is used for filtering,

[0097]

[0098]

[0099] In formula (5), κ 1 are the parameters to be designed.

[0100] (III) Design the regression matrix,

[0101]

[0102]

[0103] Among them, κ 2 are the parameters to be designed.

[0104] (iv) Calculate the adaptive rate of the unknown parameter ζ,

[0105]

[0106] In formula (7), is the estimated value of ζ, and Π is the positive definite matrix to be designed.

[0107] Step 6: Use the state predictor to calculate the system state variables without delay.

[0108]

[0109]

[0110]

[0111]

[0112] in, is the state variable of the system without time delay.

[0113] Step 7: Calculate the optimal expected value x of the radiator outlet temperature through the equilibrium point optimization module 2d , ensuring that the system energy consumption reaches the theoretical optimal value. The traversal solution algorithm is used to solve the optimization problem as follows:

[0114] min J op (x 2d ) = f 1 (u 1 (x 2d ))+f 2 (u 1 (x 2d ))

[0115] st

[0116]

[0117]

[0118]

[0119]

[0120]

[0121] In formula (9), function f 1 is a known electronic water pump power function, function f 2 is a known power function of the electronic fan. S max They are x 2d The maximum setting value of the acceptable range (manually set). It is the lower limit of the range of the electronic water pump control value. It is the upper limit of the range of the electronic water pump control value. It is the lower limit of the range of electronic fan control value. It is the upper limit of the electronic fan control value range.

[0122] Step 8: Solve the control quantity based on the state tracking controller

[0123]

[0124] u2 =1

[0125]

[0126]

[0127] In formula (10), x 1d is the expected value of the heat source outlet temperature, x 2d is the expected value at the radiator outlet. k 1 , k 2 , k 3 and k 4 is the control parameter to be designed.

[0128] The effectiveness of the control method provided by the present invention is verified through bench experiments.

[0129] like Figure 3 The figure shows the engine thermal management system experimental platform. The engine thermal management system in the experimental platform consists of a dSPACE controller, an electric water pump, an electric thermostat, a radiator, an electric fan and three temperature sensors. Through experimental measurement, the system model parameters are shown in Table 1. Through bench experiments and model identification, the power function identification of the electric water pump and electric fan is as follows

[0130] f 1 (u 1 )=2.718u 1 2 +18.5u 1

[0131] f 2 (u 3 )=36.09u 3 2 +238u 3 (11)

[0132] The thermal management system controller is constructed using the above controller design process, and the controller parameter design is shown in Table 2.

[0133] Table 1 Engine thermal management system model parameters

[0134] parameter value parameter value <![CDATA[γ 1 ]]> 0.15 <![CDATA[γ 2 ]]> 0.3555 <![CDATA[γ 3 ]]> 0.17 <![CDATA[γ 4 ]]> 0.0022 <![CDATA[γ 5 ]]> 0.9

[0135] Table 2 Engine thermal management system controller parameters

[0136] parameter value parameter value <![CDATA[κ 1 ]]> 1 <![CDATA[κ 2 ]]> 0.4 <![CDATA[k 1 ]]> 1.525 <![CDATA[k 2 ]]> 0.3 <![CDATA[k 3 ]]> 1.532 <![CDATA[k 4 ]]> 0.35 Π diag(0.1,0.3)

[0137] Two sets of experiments are conducted to verify the effectiveness of the control method.

[0138] Experiment 1: Try to keep the engine heat generation constant, use a step input signal as the expected temperature of the engine, and test the temperature tracking control performance of the controller.

[0139] In experiment 1, the air-fuel ratio of the engine was set to 15.2, and the throttle opening was set to 15 degrees, in order to keep the heat generation of the engine constant. The air-fuel ratio and throttle opening change curves are shown in Figure 4 The temperature control curves of the engine and radiator are shown in Figure 5 As shown, the temperature error change curve is as follows Figure 6 As shown. Figure 5 and Figure 6 It can be seen that the engine temperature can quickly track the expected temperature value of the upper step change, the effective adjustment time is less than 100s, and the temperature steady-state error is less than 0.2℃. The optimal expected value of the radiator outlet temperature output by the balance point optimization module is x 2d The change curve is as Figure 6 The actual control curve of the electric water pump and the control curve of the corresponding theoretical optimal energy consumption output by the balance point optimization module are shown in Figure 7 The actual control curve of the electric fan and the control curve of the corresponding theoretical optimal energy consumption output by the balance point optimization module are shown in Figure 8 As shown. Figure 6 It can be seen that the radiator outlet temperature quickly tracks the expected temperature output by the upper balance point optimization module. Figure 7 and Figure 8 It can be seen that the control curve output by the controller gradually tracks the control curve output by the upper balance point optimization module, which means that the actual energy consumption of the system reaches the theoretical optimal energy consumption value.

[0140] Experiment 2: Keep the desired engine temperature unchanged, change the heat generated by the engine, and test the controller's adaptability and interference suppression capabilities.

[0141] In experiment 2, the air-fuel ratio of the engine was set to 15.2, and the heat generation of the engine was adjusted by changing the throttle opening, such as Fig. 9 The temperature control curves of the engine and radiator are shown in Fig.10 As shown, the temperature error change curve is as follows Fig.11 As shown. Fig.10 and Fig.11 It can be seen that under changing working conditions, the engine temperature and radiator temperature can still track the expected temperature, and the temperature steady-state error is less than 0.2°C. The optimal expected value of the radiator outlet temperature output by the balance point optimization module is x 2d The change curve is as Fig.10 The actual control curve of the electric water pump and the control curve of the corresponding theoretical optimal energy consumption output by the balance point optimization module are shown in Fig.12The actual control curve of the electric fan and the control curve of the corresponding theoretical optimal energy consumption output by the balance point optimization module are shown in Fig.13 As shown. Fig.12 and Fig.13 It can be seen that the control curve output by the controller gradually tracks the control curve output by the upper balance point optimization module, which means that the actual energy consumption of the system has reached the theoretical optimal energy consumption value.

[0142] The results of Experiment 1 and Experiment 2 show that the thermal management system control strategy proposed by the present invention has high control accuracy and ensures that the system energy consumption reaches the theoretical optimal value. In addition, facing complex and changeable working conditions, the control strategy has good interference suppression ability and adaptability.

[0143] The control method of the present invention can achieve high-precision temperature control. By selecting appropriate controller parameters, the temperature steady-state error can be reduced to less than 0.3°C. The temperature regulation is dynamic and fast, and the effective regulation time is less than 100s. It can meet the setting requirements of the temperature consistency within the system and achieve a thermal management system energy consumption close to the theoretical optimal value.

[0144] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. An adaptive optimization thermal management control method for a liquid-cooled power source, Characterized in that: It includes the following steps: First, use a sampling module to obtain the heat source outlet temperature and radiator outlet temperature in the thermal management system, and the sampling module outputs power source temperature information; At the same time, the control quantity of the electric water pump is input to the delay estimator, and the delay estimator outputs the estimated system time delay. The calculation formula of the system time delay is: τ = γ 4 u 1 + γ 5 (3); Among them, γ 4 and γ 5 are system property parameters; u 1 is the control quantity of the electric water pump; Second, input the air temperature, power source temperature information, and the time delay control signal of the thermal management system actuator output by the second data stack module into the disturbance estimator, and the disturbance estimator outputs the estimated value of the uncertain parameters during the operation of the thermal management system; The calculation formula of the estimated value of the uncertain parameter is: Among them Equation (6) wherein Equation (5) wherein Among them, x 1 is the heat source outlet temperature, x 2 is the radiator outlet temperature, u 1 is the control quantity of the electric water pump, u 2 is the control quantity of the electric thermostat, u 3 is the control quantity of the electric fan, ζ 1 is the heat transferred from the heat source to the coolant, ζ 2 is the estimated deviation of the heat dissipation of the radiator, ζ i , i ∈ [1, 2] are the unknown parameters of the thermal management system, γ i , i ∈ [1, 3] are the system property parameters; κ 1 is the parameter to be designed, is the estimated value of ζ, ∏ is the positive definite matrix to be designed; x i,τ represents the state value obtained by measuring the system state after a pure time delay; Third, input the estimated value of the uncertain parameters of the thermal management system output by the disturbance estimator into the first data stack module for storage. The first data stack module outputs the information of the estimated value of the uncertain parameters of the thermal management system stored internally, and then outputs the estimated value of the uncertain parameter of the time delay by the first data stack. Input the control signal of the thermal management system actuator and the power source temperature information stored internally in the third data stack module into the system estimator, and the system estimator outputs the estimated value of the non-delay state variable. The calculation formula of the estimated value of the non-delay state variable is as follows: Among them, is the state variable of the system without time delay; At the same time, input the estimated value of the uncertain parameter output by the disturbance estimator module, the expected value of the heat source outlet temperature, the lower bound setting value of the expected radiator outlet temperature, and the air temperature into the balance point optimization module, and the balance point optimization module outputs the optimal setting value of the radiator outlet temperature; The calculation formula of the optimal setting value of the radiator outlet temperature is: Among them, the function f 1 is the known power function of the electric water pump, and the function f 2 is the known power function of the electric fan; S max are respectively the maximum setting values of the value ranges that x 2d can take; is the lower bound of the value range of the electric water pump control quantity; is the upper bound of the value range of the electric water pump control quantity; is the lower bound of the value range of the electric fan control quantity; is the upper bound of the value range of the electric fan control quantity; x 1d is the expected value of the heat source outlet temperature, and x 2d is the expected value of the radiator outlet; Fourth, input the estimated value of the uncertain parameter output by the disturbance estimator, the estimated value of the non-delay state variable output by the system estimator, the optimal setting value of the radiator outlet temperature output by the balance point optimization module, the expected value of the heat source outlet temperature, and the air temperature into the state tracking controller, and the state tracking controller outputs a signal as the control signal of the thermal management system actuator; The calculation formula of the control signal of the thermal management system actuator is: where k 1 , k 2 , k 3 and k 4 are control parameters to be designed; Input the actuator control signal output by the state tracking controller into the sub-controller of the relevant actuator in the thermal management system; at the same time, input the actuator control signal output by the state tracking controller into the second data stack module and the third data stack module for storage. The output of the second data stack module stores the time delay control signal of the thermal management system actuator internally, and the output of the third data stack stores the control signal of the thermal management system actuator internally.

2. An adaptive optimization thermal management control system based on a liquid-cooled power source, Characterized in that: The control system includes seven sub-modules that execute the control method described in claim 1, namely: The thermal management system model module is used to establish a thermal management system model to simulate the operating conditions of the thermal management system during engine operation and output the state variables of the system; The delay estimator module is used to estimate the pure time delay of the system. The input signal of the delay estimator module is the control quantity of the electric water pump, and the output signal is the estimated pure time delay of the system; A data stack module for storing the most recent consecutive input signals. The input signals of the data stack module are the control variables and status variables to be stored, and the output signal is the variable stored internally; A sampling module for collecting the temperatures at the heat source and the radiator outlet. The input signals of the sampling module are the temperature information output by the first temperature sensor and the second temperature sensor; An interference estimator module for estimating the uncertain parameters during system operation. The input signals of the interference estimator are the air temperature, the temperature information, and the time-delay control quantity information output by the first data stack, and the output signal is the estimated value of the uncertain parameters; A state predictor module for estimating the non-time-delay state variables of the system and compensating for the performance degradation of the system caused by time delay. The state predictor module consists of a second data stack and a system estimator module. The input signal of the second data stack is the actuator control quantity signal output by the state tracking controller, and the output signal is the actuator control quantity signal stored internally; the input signals of the system estimator module are the actuator control quantity stored internally output by the second data stack, the estimated value of the uncertain parameters output by the interference estimator data stack, and the temperature information, and the output signal is the estimated value of the non-time-delay state variables; An equilibrium point optimization module for calculating the optimal set value of the radiator outlet temperature corresponding to the optimal energy consumption of the system. The input signals of the equilibrium point optimization module are the expected value of the heat source outlet temperature, the lower bound set value of the expected radiator outlet temperature, the air temperature, and the estimated value of the uncertain parameters output by the interference estimator module, and the output signal is the optimal set value of the radiator outlet temperature. A state tracking controller module for calculating the control signals of the electric water pump, the electric fan, and the electric thermostat. The input signals of the state tracking controller are the air temperature, the expected value of the heat source outlet temperature, the optimal set value of the radiator outlet temperature, the estimated value of the uncertain parameters output by the interference estimator module, and the estimated value of the non-time-delay state variables output by the state predictor module, and the output signal is the control signal of the actuator of the thermal management system.

3. A thermal management system, comprising a heat source heating circuit, a heat source cooling circuit, and the control system according to claim 2.

4. The thermal management system according to claim 3, characterized in that: The described heat source heating circuit includes a heat source, an electronic thermostat, an electric water pump, and a first temperature sensor; the heat source heat dissipation circuit includes a heat source, an electronic thermostat, a radiator, an electric water pump, and a second temperature sensor; the outlet end of the water jacket inside the heat source is connected to the inlet of the first temperature sensor, and the outlet of the first temperature sensor is connected to the inlet of the electronic thermostat; the outlet 1 of the electronic thermostat is connected to the inlet 1 of the three-way valve; the outlet 2 of the electronic thermostat is connected to the inlet of the radiator; the outlet of the radiator is connected to the inlet of the second temperature sensor; the outlet of the second temperature sensor is connected to the inlet 2 of the three-way valve; the outlet of the three-way valve is connected to the inlet of the electric water pump; the outlet of the electric water pump is connected to the inlet of the water jacket inside the heat source, and the input ports of the control system 8 are respectively connected to the first temperature sensor and the second temperature sensor; the output ports are respectively connected to the sub-controller of the electronic thermostat, the sub-controller of the electric water pump, and the sub-controller of the radiator, and the control system 8 directly sends control instructions to the sub-controllers of the relevant actuators.

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