A multi-power-source electric drive energy-heat integrated system and a collaborative intelligent control method thereof

Abstract

The application discloses a kind of energy-heat integrated systems of multiple power source electric drive and its collaborative intelligent control method, energy-heat integrated system includes range extender loop, electric drive electric control loop, battery loop, heating and heating loop, air conditioning cooling and heat exchange loop and eight-way valve;Collaborative intelligent control method is: according to the importance of each power component selects thermal evaluation index, subjective evaluation and objective evaluation respectively through engineering experience, sample data determine the weight of each thermal evaluation index, after twice weighting, the comprehensive weight of each index is determined, and a thermal evaluation function is established;Combining thermal evaluation function and the energy consumption of each working component, the fuel economy and the working state of each component are comprehensively considered, and a target optimization function is established;Then, according to sample data and physical model, predictive modeling is carried out, model predictive control is used, and the optimal control amount when the target optimization function is minimized is solved, so that the tractor can reach the highest energy utilization and the best overall working performance.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of new energy tractor control, and particularly relates to an energy-heat integrated system of a multi-power-source electric drive and a collaborative intelligent control method thereof. BACKGROUND

[0002] Traditional tractors are mostly driven by diesel engines, which have large working power but low energy utilization rate. When the power system provides power for the field work of the tractor, it needs to pass through a complex transmission mechanism, and most of the traditional tractors use mechanical water pumps and fans in the thermal management system, which cannot automatically adjust the speed. The power system and the thermal management system belong to two independent systems, which are difficult to integrate and manage, the energy utilization rate of the power system is low, and the cooling capacity of the thermal management system is not fully utilized.

[0003] In recent years, with the increasing maturity of new energy vehicle technology, hybrid tractors have also developed rapidly. Compared with traditional tractors, the transmission system of hybrid tractors, especially the range-extender electric tractor, has been greatly simplified. The range-extender and the electric control system of the electric drive use advanced programmable control units, the thermal management system uses electronic water pumps and electric fans with speed self-adaptive adjustment, and the data exchange between the power system and the thermal management system is more flexible and efficient, making integrated control easier to achieve.

[0004] The power system optimizes the energy flow among multiple energy sources through energy management strategies. In work, heat is generated, and the appropriate working temperature of each power component and the generated heat are different, so that the whole machine has the characteristics of multiple heat sources and multiple temperature zones. The working components, especially the battery, are very sensitive to temperature, and large amplitude temperature change will seriously affect its working performance. Accurate thermal management is needed to ensure that it works within the appropriate temperature range, which requires the thermal management system to be more closely integrated with the power system to more effectively control each working component within the appropriate temperature range and maintain the efficient operation of each working component. At the same time, there is currently a lack of monitoring method for the thermal management performance of the whole tractor. In order to evaluate the thermal state of the whole tractor, a reasonable evaluation system needs to be established to monitor the working state of the thermal management system of the tractor in real time. SUMMARY

[0005] Therefore, the present application provides a multi-power-source electric drive energy-heat integrated system and a collaborative intelligent control method thereof, which is used for controlling the flow of energy and heat in a range-extender electric tractor and improving the energy utilization efficiency and working performance of the whole machine.

[0006] The present application achieves the above technical purpose by the following technical means.

[0007] The present application achieves the above technical purpose by the following technical means.

[0008] The electric drive electric control circuit is sequentially connected by a first water pump, a motor controller, a motor, a three-in-one, and an electric drive electric control radiator.

[0009] The range extender circuit is sequentially connected by a second water pump, a range extender, a first heat exchanger, a throttle valve, and a range extender radiator.

[0010] The battery circuit includes a third water pump, a first three-way valve, a cold air core, a second heat exchanger, and a battery pack.

[0011] The heating and warming circuit includes a PTC, a second three-way valve, a third heat exchanger, a warm air core, and a fourth water pump.

[0012] The air conditioning cooling and heat exchange circuit is sequentially connected by a compressor, a condenser, a liquid storage tank, an electronic expansion valve, a second heat exchanger, and a first heat exchanger.

[0013] The eight-way valve is provided with working ports a, b, c, d, e, f, g, and h.

[0014] The three-in-one includes a charger, a junction box, and a DC / DC converter.

[0015] The electric drive electric control radiator and the range extender radiator are both provided with a cooling fan.

[0016] The cold air core and the warm air core are both provided with a blower.

[0017] The working modes of the multi-power source electric drive energy-heat integrated system include the following: the waste heat of the electric drive electric control circuit is used for battery heating, the waste heat of the electric drive electric control circuit is used for cabin heating, the PTC is used for battery heating, the PTC is used for cabin heating, each circuit is cooled by itself, the air conditioning cooling and heat exchange circuit is used for battery pack cooling and cabin cooling, the air conditioning cooling and heat exchange circuit is used for cabin dehumidification and battery pack cooling and cabin cooling, the waste heat of the engine is used for cabin heating, and the waste heat of the engine is used for battery heating.

[0018] A kind of collaborative intelligent control method of energy-heat integrated system of multi-power source electric drive

[0019] According to the characteristics of multiple heat sources and multiple temperature zones in the energy-heat integrated system, the thermal evaluation index is selected according to the importance of each power component, the weights of each thermal evaluation index are determined by subjective evaluation and objective evaluation through engineering experience and sample data, and the comprehensive weights of each index are determined after secondary weighting, and a thermal evaluation function is established, which can reflect the thermal state of the whole machine in real time.

[0020] Combining the thermal evaluation function with the energy consumption of the working components in the energy-heat integrated system, the fuel economy and the working state of each component are comprehensively considered to establish a target optimization function; then, according to the sample data and the physical model, a predictive modeling is carried out, a model predictive control is adopted, and the optimal control amount is solved when the target optimization function is minimized, so that the tractor can achieve the highest energy utilization rate and the best overall working performance.

[0021] Further, the thermal evaluation function is:

[0022] A=ω1'ΔT1+ω2'ΔT2+…+ω9'ΔT9

[0023] Wherein, A is the final evaluation score of the whole vehicle thermal system, ΔT1 is the difference between the actual cooling liquid inlet temperature T e1 of the engine and the optimal cooling liquid inlet temperature of the engine, ΔT2 is the difference between the actual cooling liquid outlet temperature T e2 of the engine and the optimal cooling liquid outlet temperature of the engine, ΔT3 is the difference between the actual cooling liquid outlet temperature T m1 of the electric motor and the optimal cooling liquid outlet temperature of the electric motor, ΔT4 is the difference between the actual cooling liquid outlet temperature T m2 of the motor controller and the optimal cooling liquid outlet temperature of the motor controller, ΔT5 is the difference between the actual cooling liquid outlet temperature T m3 of the three-in-one and the optimal cooling liquid outlet temperature of the three-in-one, ΔT6 is the difference between the actual maximum temperature T bmax of the battery and the normal working temperature of the battery, ΔT7 is the difference between the actual cooling liquid outlet temperature of the battery pack and the optimal cooling liquid outlet temperature of the battery pack, ΔT8 is the difference between the actual maximum temperature difference T b△ of the battery surface and the normal temperature difference of the battery surface, ΔT9 is the difference between the actual temperature T c of the cockpit and the optimal temperature of the cockpit, ω1', ω2', ω3', ω4', ω5', ω6', ω7', ω8', ω9' are the weight coefficients corresponding to ΔT1, ΔT2, ΔT3, ΔT4, ΔT5, ΔT6, ΔT7, ΔT8, ΔT9 respectively.

[0024] Further, the control variable of the model predictive control is:

[0025] u = {T ICE ,T EM ,N f1 ,N f2 ,N p1 ,N p2 ,N p3 ,N p4 ,N c ,k1,k2,k3}

[0026] The state variable of the model predictive control is:

[0027] x = {SOC t ,T e1 ,T e2 ,T m1 ,T m2 ,T m3 ,T bmax ,T b1 ,T bΔ ,T c}

[0028] Wherein, T ICE is the engine torque, T EM is the motor torque, N f1 , N f2 are the rotation speeds of the electric drive electric control radiator fan and the range extender radiator fan, N p1 , N p2 , N p3 , N p4 are the rotation speeds of the first water pump, the second water pump, the third water pump and the fourth water pump, N c is the compressor rotation speed, k1 is the working state of the eight-way valve, k2 and k3 are the working states of the first three-way valve and the second three-way valve, and SOC t is the actual SOC value.

[0029] Further, the target optimization function is:

[0030]

[0031] Wherein, ξ fuel (t) represents the fuel consumption of the power system, E EMS (t) represents the electric energy consumption of the power system, E TMS (t) represents the total energy consumption of the main working components of the thermal management system, and κ1, κ2 and κ3 are the weights of the fuel consumption, the electric energy consumption and the thermal evaluation function score.

[0032] Further, in the model predictive control, the optimal control cost function of the energy-thermal integrated system is:

[0033]

[0034] wherein, is the predicted value of the target optimization function at k+j moment, u[k+i] is the control input at k+i moment, Δu[k+i] is the control input increment at k+i moment, N and N u is the number of training points selected from sample data, Q is the weight of the target optimization function, R u is the weight of the control input, R Δ is the weight of the control input increment.

[0035] The beneficial results of the present application are: the energy-thermal integrated system model of the extended-range electric tractor is built in the present application, and the power system and the thermal management system are integrated. Aiming at the characteristics of multiple heat sources of the extended-range electric tractor, a thermal evaluation function is established, a thermal evaluation index is selected, a weighted method combining subjectivity and objectivity is applied to obtain the comprehensive weight coefficient of each index, the score of the thermal evaluation system is calculated, and the current working state of the whole machine is reflected; the energy-thermal target optimization function considering the energy consumption rate and the working performance of the whole machine is established, the training sample data and the physical model are selected for prediction modeling according to the built energy-thermal integrated system, and the optimal control amount of the energy-thermal collaborative control system is solved by using model predictive control. The power system and the thermal management system of the extended-range electric tractor are integrated in the present application, the fuel economy of the power system, the economic benefit of the thermal management system and the working performance of each working component are considered, the energy and the heat are collaboratively controlled, the tractor can reach the comprehensive state of the highest energy utilization rate and the optimal working efficiency of each component, and the real-time performance and the accuracy of the control system are improved, which has positive significance for enhancing the reliability, the economy of the hybrid power system and the working life of each component. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 is the schematic diagram of the energy-thermal integrated system model of the present application;

[0037] Figure 2 is the schematic diagram of model one of the energy-thermal integrated system model of the present application;

[0038] Figure 3 is the schematic diagram of model two of the energy-thermal integrated system model of the present application;

[0039] Figure 4 is the schematic diagram of model three of the energy-thermal integrated system model of the present application;

[0040] Figure 5 is the schematic diagram of model four of the energy-thermal integrated system model of the present application;

[0041] Figure 6 is the schematic diagram of model five of the energy-thermal integrated system model of the present application;

[0042] Figure 7 Figure 6 is a schematic diagram of a model of an energy-heat integrated system of the present application;

[0043] Figure 8 Figure 7 is a schematic diagram of a model of an energy-heat integrated system of the present application;

[0044] Figure 9 Figure 8 is a schematic diagram of a model of an energy-heat integrated system of the present application;

[0045] Figure 10 Figure 9 is a schematic diagram of a model of an energy-heat integrated system of the present application;

[0046] Figure 11 Figure 10 is a block diagram of a multi-power-source electric drive energy-heat integrated system and its collaborative intelligent control of the present application;

[0047] Figure 12 Figure 11 is a flow chart of a multi-power-source electric drive energy-heat integrated system and its collaborative intelligent control of the present application;

[0048] In the figure: 1 - eight-way valve, 2 - first water pump, 3 - motor controller, 4 - electric motor, 5 - mechanical structure, 6 - three-in-one, 7 - electric drive electric control radiator, 8 - second water pump, 9 - range extender, 10 - first heat exchanger, 11 - throttle valve, 12 - range extender unit radiator, 13 - third water pump, 14 - first three-way valve, 15 - cold air core, 16 - second heat exchanger, 17 - battery pack, 18 - PTC (positive temperature coefficient thermistor), 19 - second three-way valve, 20 - third heat exchanger, 21 - warm air core, 22 - fourth water pump, 23 - compressor, 24 - condenser, 25 - liquid storage tank, 26 - electronic expansion valve. DETAILED DESCRIPTION

[0049] The present application will be further described below in conjunction with the accompanying drawings and specific embodiments, but the scope of protection of the present application is not limited thereto.

[0050] This embodiment takes a range-extended electric tractor as an example, and its thermal management system adopts an integrated thermal management system with an eight-way valve. The energy-heat integrated system model composed of the power system and the thermal management system is shown in Figure 6. Figure 1

[0051] The energy-heat integrated system model is composed of a range extender circuit, an electric drive electric control circuit, a battery circuit, a heating and warming circuit, and an air conditioning cooling and heat exchange circuit. The range extender 9, the battery pack 17, the motor controller 3, and the electric motor 4 are electrically connected to form the whole machine power system, and other components in the model are responsible for maintaining the power system at the optimal working temperature to achieve the best working performance.

[0052] ​The electric drive electric control circuit is connected by a first water pump 2, a motor controller 3, a motor 4, a three-in-one 6, and an electric drive electric control radiator 7 in sequence; the motor controller 3 receives power provided by the range extender 9 and the battery pack 17, and accurately controls the motor 4; the motor 4 is the main power component in the circuit, and provides power for the mechanical structure 5 of the tractor; the optimal working temperature of the charger, the junction box, and the DC / DC converter is similar, so they are collectively referred to as "three-in-one"; the first water pump 2 provides power for the circulation of the coolant in the circuit; the electric drive electric control radiator 7 is provided with a cooling fan, which can cool the coolant flowing through the radiator.

[0053] The range extender circuit is connected by a second water pump 8, a range extender 9, a first heat exchanger 10, a throttle valve 11, and a range extender radiator 12 in sequence; the range extender 9 is composed of an engine and a generator, and generates electricity by driving the generator, and provides power to the motor 4, which is the main power component in the circuit; the first heat exchanger 10 exchanges heat between the circuit and the air conditioning cooling and heat exchange circuit, and realizes waste heat recovery; the throttle valve 11 adjusts the opening according to the temperature of the coolant, and realizes the switching of large / small circulation; the second water pump 8 provides power for the circulation of the coolant in the circuit; the range extender radiator 12 is provided with a cooling fan, which can cool the coolant flowing through the radiator. The range extender circuit is divided into large / small circulation cooling modes according to the current working temperature of the engine. When the engine temperature is low, the engine enters the small circulation cooling mode, at this time, in order to ensure that the engine is quickly warmed up to the normal working temperature, the throttle valve 11 is closed, the coolant does not pass through the range extender radiator 12, and the heat loss is reduced; when the engine temperature reaches a certain threshold, the throttle valve 11 is opened, and the engine enters the large circulation cooling mode, at this time, the engine coolant needs the radiator fan to meet the cooling demand of the engine.

[0054] The battery circuit includes a third water pump 13, a first three-way valve 14, a cold air core 15, a second heat exchanger 16, and a battery pack 17; the third water pump 13 is connected with the cold air core 15 and the second heat exchanger 16 through the first three-way valve 14, and then connected with the battery pack 17; the battery pack 17 provides power for the motor 4, and is sensitive to temperature changes, which is the main power component in the circuit, and needs to be maintained in the optimal working temperature range as much as possible; the third water pump 13 provides power for the circulation of the coolant in the circuit; the first three-way valve 14 has three ports, in the figure, the left side in the horizontal direction is the first port, the right side is the second port, and the vertical direction is the third port; by controlling the opening and closing of the ports, the flow direction of the coolant in the circuit can be controlled; the cold air core 15 is provided with a blower, which can blow cold air into the cabin to cool when the coolant with low temperature flows through the cold air core 15; the second heat exchanger 16 exchanges heat between the circuit and the air conditioning cooling and heat exchange circuit, and realizes waste heat recovery.

[0055] The heating and warming circuit comprises a PTC 18, a second three-way valve 19, a third heat exchanger 20, a warm air core 21, and a fourth water pump 22. The PTC 18 is connected to the third heat exchanger 20 and the warm air core 21 through the second three-way valve 19, and then connected to the fourth water pump 22. The PTC 18 is a heating element in the circuit. When the PTC 18 is turned on in a low-temperature environment, each circuit can be heated through the eight-way valve 1. The second three-way valve 19 has three ports. In the figure, the left port in the horizontal direction is the first port, the right port is the second port, and the vertical port is the third port. The flow direction of the coolant in the circuit can be controlled by controlling the opening and closing of the ports. The third heat exchanger 20 exchanges heat between the circuit and the air conditioning cooling and heat exchange circuit, achieving waste heat recovery. The warm air core 21 is equipped with a blower. When the coolant with high temperature flows through the warm air core 21, the blower can blow cold air into the cabin for warming. The fourth water pump 22 provides power for the circulation of the coolant in the circuit.

[0056] The air conditioning cooling and heat exchange circuit comprises a compressor 23, a condenser 24, a liquid tank 25, an electronic expansion valve 26, a second heat exchanger 16, and a first heat exchanger 10 connected in sequence. The condenser 24 is connected to the third heat exchanger 20. The compressor 23 compresses the cooling medium in the circuit into a high-temperature and high-pressure gas, which becomes a low-temperature and high-pressure liquid after condensation by the condenser 24, and then becomes a low-temperature and low-pressure gas after flowing through the liquid tank 25 and the electronic expansion valve 26. The gas then flows through the second heat exchanger 16 and the first heat exchanger 10 to exchange heat with other circuits.

[0057] The eight-way valve 1 has eight working ports, namely working port a, working port b, working port c, working port d, working port e, working port f, working port g, and working port h. The two ends of the electric drive electric control circuit are connected to the working ports a and b, respectively. The two ends of the range extender circuit are connected to the working ports c and d, respectively. The two ends of the battery circuit are connected to the working ports e and f, respectively. The two ends of the heating and warming circuit are connected to the working ports g and h, respectively. According to the cooling requirements of the power system, the connection mode between the eight working ports can be adjusted to switch between different modes, realizing integrated management of the five circuits.

[0058] According to the power demand of the energy-heat integrated system under different working conditions, the power system has three working modes. For these three working modes, the remaining working components of each circuit work cooperatively to maintain the working components of the power system within the optimal working temperature range. The three modes of the power system are:

[0059] (1) Pure electric mode.

[0060] In this mode, the motor 4 is driven by the battery pack 17 alone to provide power for the tractor, which is mainly used in the case of high battery SOC and road and field walking working conditions. In this mode, the energy-heat integrated system has the following modes:

[0061] Mode one: the waste heat of the electric drive and control circuit is used for battery heating.

[0062] As shown in Figure 2 , in a low temperature environment, when the battery temperature is lower than the appropriate working temperature, the electric drive and control circuit is connected with the battery circuit through the eight-way valve 1, that is, the working ports a and f of the eight-way valve 1 are connected, the working ports b and e are connected, the first port and the second port of the first three-way valve 14 are opened, the cooling liquid flows through the motor controller 3, the motor 4, and the three-in-one 6 of the electric drive and control circuit through the first water pump 2 of the electric drive and control circuit, absorbs the heat of the electric drive and control circuit, and then flows through the battery pack 17 of the battery circuit through the second water pump 13 of the battery circuit to heat the battery pack, and finally flows back to the electric drive and control circuit again to heat the power battery by using the waste heat of the electric drive and control circuit. At this time, the electric drive and control radiator 7 and the second heat exchanger 16 in the circuit do not work.

[0063] Mode two: the waste heat of the electric drive and control circuit is used for cabin heating.

[0064] As shown in Figure 3 , when the cabin temperature is low, the electric drive and control circuit, heating and heating circuit are connected through the eight-way valve 1, that is, the working ports a and h of the eight-way valve 1 are connected, the working ports b and g are connected, the first port and the second port of the second three-way valve 19 are opened, the cooling liquid flows through the motor controller 3, the motor 4, and the three-in-one 6 of the electric drive and control circuit through the first water pump 2 of the electric drive and control circuit, absorbs the heat of the electric drive and control circuit, flows through the warm air core 21, and the fourth water pump 22, and finally flows back to the electric drive and control circuit again; the warm air is blown into the cabin through the air blower added to the warm air core 21, and the waste heat of the electric drive and control circuit is used for cabin heating. At this time, the electric drive and control radiator 7, the PTC 18, the third heat exchanger 20, and the condenser 24 do not work.

[0065] Mode three: PTC is used to heat the battery.

[0066] As shown in Figure 4 , in a low temperature environment, and when the electric drive and control circuit temperature is low, the battery circuit, heating and heating circuit are connected through the eight-way valve 1, that is, the working ports e and h of the eight-way valve 1 are connected, the working ports f and g are connected, the first port and the second port of the first three-way valve 14 are opened, the second port and the third port of the second three-way valve 19 are opened, the PTC 18 is started to heat, the cooling liquid flows through the PTC 18 to absorb heat, flows through the battery pack 17 through the fourth water pump 22 of the heating and heating circuit and the third water pump 13 of the battery circuit, and directly heats the battery through the PTC 18. At this time, the second heat exchanger 16 and the third heat exchanger 20 do not work.

[0067] Mode 4: PTC for cockpit heating.

[0068] like Figure 5 As shown, when the ambient temperature is low and neither the electric drive control circuit nor the battery circuit has reached a suitable operating temperature, the PTC18 heats the heating and warming circuit. That is, the working ports g and h of the eight-way valve are connected, and the first and second ports of the second three-way valve 19 are opened. The coolant absorbs the heat generated by the PTC18 and carries the heat to the heater core 21. The blower installed in the heater core 21 blows the warm air into the cockpit, and the PTC is used to heat the cockpit separately.

[0069] Mode 5: Each circuit is self-cooled.

[0070] like Figure 6 As shown, when each circuit can meet its own thermal management requirements and the cockpit does not require cooling or heating, the circuits are connected via an eight-way valve. Specifically, the working ports a and b of the eight-way valve 1 are connected, c and d are connected, and e and f are connected. The first and second ports of the three-way valve 14 are open, and each circuit cools itself. The coolant in the electric drive and control circuit and the range extender circuit is cooled by the radiator fans on the electric drive and control radiator 7 and the range extender unit radiator 12, respectively. At this time, the first heat exchanger 10 and the second heat exchanger 16 are not working.

[0071] Mode 6: The air conditioning cooling and heat exchange circuit is used for battery pack cooling and cockpit cooling.

[0072] like Figure 7 As shown, the working ports e and f of the eight-way valve 1 are connected, and the first, second, and third ports of the three-way valve 14 are interconnected. The cooling medium is compressed into a high-temperature and high-pressure gas by the compressor 23, and then converted into a low-temperature and low-pressure liquid by the condenser 24. It flows through the liquid storage tank 25 and becomes a low-temperature and low-pressure gas after passing through the electronic expansion valve 26. The heat generated by the battery circuit is absorbed by the cooling medium in the air conditioning cooling and heat exchange circuit through the second heat exchanger 16. Driven by the third water pump 13 of the battery circuit, the cooled coolant flows through the battery pack 17 and the cold air core 15. The blower installed at the cold air core 15 blows the cold air into the cockpit, thereby cooling the battery pack 17 and the cockpit.

[0073] Mode 7: The air conditioning cooling and heat exchange circuit is used for cockpit dehumidification, battery pack cooling, and cockpit cooling.

[0074] like Figure 8As shown, the working ports e and f of the eight-way valve 1 are connected, and g and h are connected. The first, second, and third ports of the first three-way valve 14 are interconnected. The first, second, and third ports of the second three-way valve 19 are interconnected. The cooling medium is compressed into a high-temperature, high-pressure gas by the compressor 23, and then converted into a low-temperature, low-pressure liquid by the condenser 24. The released heat is absorbed by the third heat exchanger 20. Under the action of the fourth water pump 22, the heat flows through the warm air core 21, which regulates the temperature. The blower blows warm air into the cockpit for dehumidification; the condensed cooling medium flows through the liquid storage tank 25 and becomes a low-temperature, low-pressure gas after passing through the electronic expansion valve 26. The heat generated by the battery circuit is absorbed by the cooling medium in the air conditioning cooling and heat exchange circuit through the second heat exchanger 16. Driven by the third water pump 13, the cooled coolant flows through the battery pack 17 and the cold air core 15. The blower installed at the cold air core 15 blows cold air into the cockpit, thereby cooling the battery pack 17 and the cockpit.

[0075] (2) Range extender independent drive mode.

[0076] In the range extender's standalone drive mode, the engine drives the generator to produce electricity, which in turn drives the electric motor 4 and charges the battery pack 17. This mode is primarily used in applications with low battery SOC and low-power field operations. In this mode, the energy-thermal integrated system offers the following modes:

[0077] Mode 8: Engine waste heat is used for cockpit heating.

[0078] like Figure 9 As shown, when the tractor is first started in cold weather, the temperature in the cab is low. The range extender 9 can be activated to warm the cab. The working ports c and d of the eight-way valve are connected, and g and h are connected. The first, second, and third ports of the second three-way valve 19 are interconnected. At this time, the range extender 9 is activated to generate heat. Driven by the second water pump 8 in the range extender circuit, the coolant flows through the range extender 9 to absorb the heat generated by the engine. The cooling medium in the air conditioning cooling and heat exchange circuit absorbs heat at the first heat exchanger 10. The cooling medium is compressed into a high-temperature, high-pressure gas by the compressor 23, and then converted into a low-temperature, low-pressure liquid by the condenser 24. It flows through the liquid tank 25, and after passing through the electronic expansion valve 26, it becomes a low-temperature, low-pressure gas again, returning to the first heat exchanger 10 to absorb heat. At the same time, the third heat exchanger 20 absorbs heat, and under the action of the fourth water pump 22, it flows through the heater core 21. The blower installed in the heater core 21 blows warm air into the cab to warm it. At this time, neither the range extender unit heat sink 12 nor the PTC18 is working.

[0079] Mode 9: Engine waste heat is used for battery heating.

[0080] like Figure 10As shown, the temperature of the battery pack 17 is low when the tractor is started in cold weather, and the range extender 9 can be started to warm the battery pack 17. The eight-way valve is connected between ports c and d and between ports e and f, and the first port and the second port of the three-way valve 14 are connected. The range extender 9 is started to generate heat, and under the drive of the second water pump 8 in the range extender circuit, the coolant flows through the range extender 9 to absorb the heat generated by the engine. The cooling medium in the air conditioning cooling and heat exchange circuit absorbs heat at the first heat exchanger 10, and the cooling medium is compressed into a high-temperature and high-pressure gas by the compressor 23. Under the drive of the third water pump 13 in the battery circuit, the coolant absorbs heat at the second heat exchanger 16, flows through the battery pack 17 to be heated, and the cooling medium in the air conditioning cooling and heat exchange circuit returns to the first heat exchanger 10 to absorb heat. At this time, the range extender radiator 12, the second heat exchanger 16, the condenser 24, the liquid storage tank 25, and the electronic expansion valve 26 are not working.

[0081] Modes two, four, five, mode six air conditioning cooling and heat exchange circuit for cockpit cooling, and mode seven air conditioning cooling and heat exchange circuit for cockpit dehumidification cooling, in the range extender alone driving mode can also be achieved, hereinafter will not be repeated.

[0082] (3) Hybrid driving mode.

[0083] The hybrid driving mode is provided with power by the engine and the battery, and is mainly used in high-power and heavy-load working conditions. The above-mentioned nine working modes of the energy-heat integrated system can be realized according to the working conditions and the requirements of the controller in this mode, and will not be repeated here.

[0084] The main energy-consuming components of the thermal management system in the energy-heat integrated system model are the water pump, the cooling fan, and the compressor 23 in the circuit, and the energy consumption is shown in formula (1), formula (2), formula (3), and formula (4). Wherein, E pump is the power consumption of the water pump, E com is the power consumption of the compressor, E fan is the power consumption of the cooling fan, k pump is the energy consumption factor of the water pump, D pump is the maximum displacement of the water pump, p ω is the density of the coolant, N p is the rotating speed of the water pump, k fan is the energy consumption factor of the cooling fan, D fan is the maximum displacement of the water pump, C flow is the flow coefficient, p a is the density of the coolant, N f is the rotating speed of the cooling fan, V com is the displacement of the compressor, v com is the specific volume of the compressor when sucking, and l is the volumetric efficiency of the compressor, N c is the rotating speed of the compressor, w sA is a constant, here 1.66x10 -8 , N c is the compressor speed.

[0085]

[0086] The total energy consumption of the main working components of the thermal management system is:

[0087]

[0088] E fan1 is the power consumption of the electric drive electric control cooling fan, E fan2 is the power consumption of the range extender cooling fan, η fan1 is the working efficiency of the electric drive electric control cooling fan, η fan2 is the working efficiency of the range extender cooling fan, E pumpz is the power consumption of the zth water pump, η fanz is the working efficiency of the zth water pump, η com is the working efficiency of the compressor, η b1 is the battery discharge efficiency, H f is the low heat value of the fuel.

[0089] The total energy consumption of the main working components of the thermal management system is used to construct the target optimization function.

[0090] A synergistic intelligent control method for a multi-power-source electric drive energy-thermal integrated system, comprising:

[0091] A thermal evaluation function is established that can reflect the thermal state of the entire machine in real time, in view of the characteristics of multiple heat sources and multiple temperature zones in the energy-thermal integrated system.

[0092] Combining the thermal evaluation function and the energy consumption of the working components in the energy-thermal integrated system, the fuel economy and the working state of each component are comprehensively considered, and a target optimization function is established. Then, sample data and physical models are used for prediction modeling, model predictive control is adopted, and the optimal control amount at which the target optimization function is minimized is solved, so that the tractor can achieve the highest energy utilization rate and the best overall working performance.

[0093] I. Thermal evaluation function

[0094] According to the actual temperature T of each working component, a thermal evaluation index is selected, and a thermal evaluation function is established to evaluate the current overall working state.

[0095] The thermal evaluation function mainly selects the following 9 thermal evaluation indexes. The actual cooling liquid inlet temperature T e1 of the engine and the actual cooling liquid outlet temperature T e2The current working state of the range extender circuit can be reflected, and the cooling performance of the range extender circuit can be diagnosed; the actual cooling liquid outlet temperature T of the motor 4 m1 The actual cooling liquid outlet temperature T of the motor controller 3 m2 The actual cooling liquid outlet temperature T of the three-in-one 6 m3 The current cooling capacity of the electric drive control circuit can be reflected, and the working state and thermal efficiency of the equipment can be reflected; the actual maximum temperature T of the battery bmax The actual cooling liquid outlet temperature T of the battery pack b1 The actual maximum surface temperature difference T of the battery b△ The current cooling capacity of the battery circuit can be reflected, and the maximum temperature T of the battery bmax The cooling liquid outlet temperature T of the battery pack b1 The health status and safety performance of the battery can be reflected, and the maximum surface temperature difference T of the battery can be reflected b△ The consistency and thermal distribution uniformity of the battery pack can be reflected; the actual temperature T of the cockpit c The current tractor cockpit comfort can be reflected. Therefore, the nine thermal indicators are selected as the vehicle thermal evaluation function, and the difference ΔT between the current working temperature and the optimal working temperature is used as the basis for subsequent construction of the vehicle thermal evaluation function.

[0096] The distribution of the weight coefficient is another key factor in constructing the thermal evaluation function. The distribution of the weight coefficient of each index in the existing method is mostly based on engineering experience, that is, the subjective weighting method. The subjective weighting method is simple to operate and can establish a target function with a targeted approach, but the weight coefficient distributed in this way has poor adaptability to actual working conditions. The objective weighting method mainly relies on a large amount of data and summarizes the degree of change of each index to determine the weight, which is more scientific and intuitive. However, the objective weighting method only relies on the data of the index itself to make judgments, and cannot accurately reflect the preferences of the decision maker and the influence of the index on other systems, resulting in weak explainability of the weight. In the thermal management system, there are temperature-sensitive components such as batteries, and their working performance is more affected than other components under the same temperature fluctuation, so the weight of these components needs to be considered. At this time, the subjective evaluation method is needed, and according to the actual engineering experience, the weight of these components is tilted, and the influence of the temperature change of each working component on other working components is considered to reasonably set the weight coefficient of each index. The combination of the two evaluation methods can better evaluate the thermal system by combining objective experimental data and subjective engineering experience. Therefore, a weight coefficient distribution method combining subjective and objective methods is designed here.

[0097] (1) The objective weight coefficient is distributed according to the degree of change of each thermal evaluation index in the training working condition data.

[0098] Collect N groups of original training sample data sets for analysis, including:

[0099] First, standardize the data:

[0100]

[0101] Among them, is the average value of the jth index, D j is the corresponding variance, △T ij is the jth index value of sample i (i = 1, 2, …, N; j = 1, 2, …, n);

[0102] Then, the standardized data is non-negative:

[0103]

[0104] Then, the above data is used to calculate the weight of each index, which is specifically divided into:

[0105] 1) Calculate the information entropy

[0106] The information entropy of the jth index is calculated as follows:

[0107]

[0108] Among them, c ij is the change degree of each index, that is, the proportion of the index value of the ith sample under the jth index, and

[0109] 2) Calculate the weight of each index

[0110] The weight coefficient of each index is determined as follows:

[0111]

[0112] Finally, the objective weight vector ω1=(ω 11 ,ω 12 ,…,ω 1n ) is obtained.

[0113] (2) The allocation of subjective weight coefficient combines intuitive fuzzy numbers, decision experiments and evaluation experiments to determine the importance between elements. The weighting process of each index is:

[0114] 1) Construct a language evaluation set

[0115] This embodiment uses a five-scale language evaluation set to describe the influence degree of each index. According to the sensitivity of each working component to temperature change, the constructed language evaluation set is shown in Table 1.

[0116] Table 1 Value language variables and their intuitionistic fuzzy numbers

[0117]

[0118] 2) Constructing fuzzy influence matrix

[0119] Firstly, P experts determine the influence degree between each index according to the influence degree between each index in engineering experience through the language evaluation set, and then convert the judgment results into corresponding fuzzy numbers, thus obtaining the influence matrix:

[0120]

[0121] Where n represents the number of indexes to be evaluated, is the influence degree of temperature change of index a on index b selected by expert p, according to the language value it wants to express, the corresponding related intuitionistic fuzzy number is selected,

[0122] Secondly, all the influence matrices are integrated to form the overall direct influence matrix:

[0123]

[0124] Where P is the total number of experts;

[0125] 3) De-fuzzification and standardization

[0126] In order to further quantify the information, the elements in are de-fuzzified to obtain the real direct influence matrix X:

[0127]

[0128] Where,

[0129] Then, the matrix X is standardized:

[0130]

[0131] Determine the comprehensive influence matrix T:

[0132] T = [t ab ] n×n = Y(1-Y) -1 (13)

[0133] Where t ab represents the comprehensive influence of index a on index b when the temperature changes.

[0134] 4) Calculate the centrality and cause degree of each index

[0135] First, calculate the degree of influence R of each indicator. a And the degree of impact C b :

[0136]

[0137] The degree of influence R of each indicator a And the degree of impact C b Obtain the weight coefficients ω of each indicator 2b :

[0138]

[0139] Based on the above process, the weight coefficients of each indicator in the subjective evaluation system were determined, and the subjective weight vector was finally obtained.

[0140] (3) The weight coefficients of each indicator are then reassigned using a game theory-based combined weighting method. This method can achieve a balance between subjective and objective factors, thus improving the scientific rationality of the weighted decision-making process to some extent. The weights are reassigned using game theory as follows:

[0141]

[0142] Where L is the number of weighting methods in a single iteration, ω l Let be the weight vector obtained by the l-th weighting method. For ω l Secondary allocation of weights, In this embodiment, two methods were used to weight the indicators, so L = 2.

[0143] The weight vector after double weighting can be determined as follows:

[0144]

[0145] Among them, ω'=(ω'1,ω'2,…,ω' n ).

[0146] The deviation between the objective weights and subjective weights after double weighting is minimized, thus balancing the importance of the indicators reflected by the objective weights and subjective weights.

[0147] Finally, the thermal evaluation function for the vehicle's thermal management is obtained as follows:

[0148] A=ω1'ΔT1+ω2'ΔT2+…+ω9'ΔT9 (19)

[0149] Where A is the final evaluation score of the vehicle's thermal system, ω n(n=1…9) is the weight coefficient of each index, ΔT1 is the difference between the actual cooling liquid inlet temperature of the engine and the optimal cooling liquid inlet temperature of the engine, ΔT2 is the difference between the actual cooling liquid outlet temperature of the engine and the optimal cooling liquid outlet temperature of the engine, ΔT3 is the difference between the actual cooling liquid outlet temperature of the electric motor and the optimal cooling liquid outlet temperature of the electric motor, ΔT4 is the difference between the actual cooling liquid outlet temperature of the motor controller and the optimal cooling liquid outlet temperature of the motor controller, ΔT5 is the difference between the actual cooling liquid outlet temperature of the three-in-one and the optimal cooling liquid outlet temperature of the three-in-one, ΔT6 is the difference between the actual maximum temperature of the battery and the normal working temperature of the battery, ΔT7 is the difference between the actual cooling liquid outlet temperature of the battery pack and the optimal cooling liquid outlet temperature of the battery pack, ΔT8 is the difference between the actual maximum surface temperature difference of the battery and the normal surface temperature difference of the battery, and ΔT9 is the difference between the actual temperature of the cockpit and the optimal temperature of the cockpit.

[0150] The final evaluation value can reflect the comprehensive state of the tractor thermal management system. The smaller the value, the smaller the deviation between the actual working temperature of each power component and the optimal working temperature, and the better the performance of the thermal management system. The larger the value, the greater the deviation between the overall temperature of the thermal management system and the optimal temperature, and the worse the performance of the thermal management system.

[0151] II. Target optimization function

[0152] The target optimization function is established, and model predictive control is used to solve it, outputting the optimal control amount when the target optimization function is minimized, to realize collaborative intelligent control of the energy-thermal integrated system.

[0153] The target optimization function combines the energy consumption of the power system, the energy consumption of the thermal management system, and the score of the thermal evaluation function, and comprehensively considers the energy consumption and working state of each component during the working process of the tractor. The target optimization function is as follows:

[0154]

[0155] wherein, ξ fuel (t) represents the fuel consumption of the power system, E EMS (t) represents the electric energy consumption of the power system, κ1, κ2, and κ3 are the weights of fuel consumption, electric energy consumption, and the score of the thermal evaluation function.

[0156] Here, the model predictive control based on the physical information neural network is used to solve the target optimization function. The model predictive control has strong robustness and dynamic response capability, and can directly incorporate system constraints into the controller design, making it suitable for various operating scenarios. However, due to the complexity of the control target in the energy-heat integrated system, a large amount of accurate data model is required for learning, and the modeling cost is too high. Therefore, the physical information neural network is introduced here, which combines physical modeling with sample data, adds a physical loss term in the machine learning process, so that the model can meet the physical constraints even with less training data, reducing the training cost of the neural network and improving the modeling accuracy.

[0157] The physical information neural network combines sample data with physical modeling, and embeds prior knowledge in the neural network through physical modeling, so that the neural network can use a smaller data set for training, improving the modeling accuracy and accelerating the convergence of the neural network.

[0158] According to the control object of the energy-heat integrated system, the control variables are selected as:

[0159] u={T ICE ,T EM ,N f1 ,N f2 ,N p1 ,N p2 ,N p3 ,N p4 ,N c ,k1,k2,k3}(21)

[0160] Where T ICE is the engine torque, T EM is the motor torque, N f1 , N f2 are the speeds of the electric drive electric control radiator fan and the range extender radiator fan, respectively, N p1 , N p2 , N p3 , N p4 are the speeds of the first, second, third and fourth water pumps, respectively, N c is the compressor speed, k1 is the working state of the eight-way valve, and k2, k3 are the working states of the first and second three-way valves, respectively.

[0161] The state variables are selected as:

[0162] x={SOC t ,T e1 ,T e2 ,T m1 ,T m2 ,T m3 ,T bmaxT b1 T bΔ T c}(22)

[0163] wherein SOC t is the actual SOC value.

[0164] According to the control variable and state variable determined above, modeling is carried out in combination with the following physical formula.

[0165] When each circuit is cooled separately, the outlet water temperature of each working component changes as follows:

[0166]

[0167] wherein, is the change rate of the outlet water temperature of each working component cooling liquid with respect to time, C C is the heat capacity of each component, Q i is the working heat production of each component, Q r is the heat dissipation power of the radiator, Q amb is the environmental heat dissipation power.

[0168] When the engine waste heat is used to heat the battery pack, the outlet water temperature of the battery pack cooling liquid changes as follows:

[0169]

[0170] wherein C Cbat is the heat capacity of the battery, is the change rate of the outlet water temperature of the battery pack cooling liquid with respect to time, Q bat is the heat production rate of the battery, δ1 and δ2 are the heat exchange efficiencies of the first and second heat exchangers respectively, Q ICE is the heat production rate of the engine, Q r2 is the power of the range-extending unit radiator.

[0171] When the waste heat of the electric drive electric control circuit is used to heat the battery pack, the outlet water temperature of the battery pack cooling liquid changes as follows:

[0172]

[0173] wherein Q EM is the heat production power of the motor, Q r1 is the power of the electric drive electric control radiator.

[0174] When the PTC is used to heat the battery pack, the outlet water temperature of the battery pack cooling liquid changes as follows:

[0175]

[0176] wherein Q PTC is the power of the PTC.

[0177] Heat sink heat dissipation power Q r :

[0178]

[0179] Wherein, a1, a2, σ1, σ2, σ3 are undetermined coefficients, t d is the time for the coolant to flow from the heat sink to each working component, and v is the vehicle speed.

[0180] Ambient heat dissipation power Q amb :

[0181] Q amb = ShΔt m (28)

[0182] Wherein, S is the heat transfer area of the heat sink, h is the convective heat transfer coefficient, and Δt m is the temperature difference.

[0183] Engine heat generation rate Q ICE :

[0184]

[0185] Wherein, is the fuel consumption rate, h f is the heat value of fuel, and η ice is the engine thermal efficiency.

[0186] Battery heat generation rate Q bat :

[0187]

[0188] Wherein, I bat is the battery current, R bat is the battery internal resistance, T bat is the battery temperature, and V oc is the open-circuit voltage of the battery.

[0189] Motor heat generation rate Q EM is:

[0190]

[0191] Wherein, I win is the motor winding phase current, R win is the motor winding internal resistance, C v , C h , C e are the electromagnetic eddy current loss coefficient, hysteresis loss coefficient, and additional loss coefficient, respectively, is the equivalent magnetic field alternating frequency, is the equivalent magnetic flux density.

[0192] Rate of change of SOC of power battery:

[0193]

[0194] Where R is the equivalent internal resistance, P bat C represents the power of the battery, and C represents the battery capacity.

[0195] Motor power P EM With engine power P ICE :

[0196]

[0197] Where, n EM η is the motor speed. EM For the efficiency of the electric motor, n ICE For engine speed, η ICE For engine efficiency.

[0198] The above physical formula model was combined with the collected sample data to train the neural network. M sets of original training sample datasets were collected for normal working cycle, winter low-temperature working cycle, and summer high-temperature working cycle, respectively, for training the neural network.

[0199] In model predictive control, the controlled system is described as:

[0200] x(k+1)=f(x(k),u(k))(35)

[0201] Where x(k+1) is the system state at time k+1, f is the system dynamic equation, and u(k) is the control input at time k.

[0202] Based on the model predictive control scheme, at each time k, the motion process of the energy-thermal integrated system is predicted over the next M time ranges, and the cost function is minimized to obtain the optimal control quantity.

[0203] The physical information neural network integrates training sample data and the control physics model into the training process by embedding partial differential equations into the loss function of the neural network. The loss function is constructed here:

[0204] L = α data L data +α phys L phps (36)

[0205] Where, α data and α phys These are weighting factors that balance the data-driven loss L. data And the loss L of the physical model phys, by adjusting the weights, to ensure that both the training sample data and the physical law are fully represented in the training process.

[0206] Data-driven loss L data The mean square error of the network prediction value and the actual observation value is:

[0207]

[0208] where N data is the sample data set of the data-driven term, is an approximate mapping of the system state to time, control input and initial state, and p is a given parameter range.

[0209] Loss L of the physical model phys The calculated mean square error is:

[0210]

[0211] where N phys is the sample data set of the physical model term, and the approximate mapping and its derivative are inserted into F, to represent the difference between the predicted state change and the actual state change.

[0212] The physical information neural network is combined with model predictive control, where the former is responsible for prediction and modeling. The initial state output in the neural network is the final state of the previous sampling interval, and the input quantity remains unchanged in this interval, obtaining the function of the next time:

[0213]

[0214] where x[k] represents the output of a single time interval, u[k] represents the control input which remains unchanged in this interval, is the interface of the physical information neural network and model predictive control, which provides the model and the prediction of the state variable for model predictive control.

[0215] After training, the physical information neural network is applied as a model in model predictive control, replacing In model predictive control, the optimal control cost function of the energy-heat integrated system is:

[0216]

[0217] where, is the predicted value of the target optimization function at k+j, u[k+i] is the control input at k+i, Δu[k+i] is the control input increment at k+i, N and N uis the number of training points selected from the training sample data, Q is the weight of the target optimization function, R u is the weight of the control input, R Δ is the weight of the control input increment.

[0218] After each loop iteration, the control variable u is input into the energy-heat integrated system model and the physics-informed neural network to achieve optimal control of the energy-heat integrated system, while updating the neural network so that the system modeling is more perfect and the prediction of the system state is more accurate.

[0219] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "exemplary embodiment", "example", "specific example" or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the exemplary description of the above terms does not necessarily mean the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0220] The embodiments are preferred embodiments of the present application, but the present application is not limited to the above embodiments, and any obvious improvements, replacements or modifications made by those skilled in the art without departing from the essential content of the present application shall fall within the protection scope of the present application.

Claims

1. A collaborative intelligent control method for a multi-power-source electric drive energy-heat integrated system, characterized in that: in view of the characteristics of multiple heat sources and multiple temperature zones in the energy-heat integrated system, a thermal evaluation index is selected according to the importance of the power components, a subjective weight vector is obtained through subjective evaluation, an objective weight vector is obtained through objective evaluation, the weight of the thermal evaluation index is determined, the subjective weight and the objective weight are twice weighted by a game theory combined weighting method to determine the comprehensive weight of the thermal evaluation index, and a thermal evaluation function capable of reflecting the thermal state of the entire machine in real time is established; the power components include an electric motor (4), a range extender (9), and a battery pack (17); a target optimization function is established by combining the thermal evaluation function with the energy consumption of the working components in the energy-heat integrated system and comprehensively considering fuel economy and the working state of the working components; then, a prediction model is established according to sample data and a physical model, model predictive control is adopted, and the optimal control amount at which the target optimization function is minimized is solved; the thermal evaluation function is: A = ω1' ΔT1 + ω2' ΔT2 + … + ω9' ΔT9 the control variable of the model predictive control is: Wherein, A is the final evaluation score of the whole vehicle thermal system, ΔT1 is the difference between the actual engine coolant inlet temperature T e1 and the optimal engine coolant inlet temperature, ΔT2 is the difference between the actual engine coolant outlet temperature T e2 and the optimal engine coolant outlet temperature, ΔT3 is the difference between the actual motor coolant outlet temperature T m1 and the optimal motor coolant outlet temperature, ΔT4 is the difference between the actual motor controller coolant outlet temperature T m2 and the optimal motor controller coolant outlet temperature, ΔT5 is the difference between the actual three-in-one coolant outlet temperature T m3 and the optimal three-in-one coolant outlet temperature, ΔT6 is the difference between the actual battery maximum temperature T bmax and the normal working temperature of the battery, ΔT7 is the difference between the actual battery pack coolant outlet temperature T b1 and the optimal battery pack coolant outlet temperature, ΔT8 is the difference between the actual battery surface maximum temperature difference T △b and the normal temperature difference of the battery surface, ΔT9 is the difference between the actual cabin temperature T c and the optimal cabin temperature, ω1', ω2', ω3', ω4', ω5', ω6', ω7', ω8', ω9' are the comprehensive weight coefficients corresponding to ΔT1, ΔT2, ΔT3, ΔT4, ΔT5, ΔT6, ΔT7, ΔT8, ΔT9 respectively. the state variable of the model predictive control is: u = {T ICE ,T EM ,N f1 ,N f2 ,N p1 ,N p2 ,N p3 ,N p4 ,N c ,k1,k2,k3} the target optimization function is: x = {SOC t ,T e1 ,T e2 ,T m1 ,T m2 ,T m3 ,T bmax ,T b1 ,T Δb ,T c} Wherein, T ICE is the engine torque, T EM is the motor torque, N f1 , N f2 are the rotation speeds of the electric drive electric control radiator fan and the range extender radiator fan, respectively, N p1 , N p2 , N p3 , N p4 are the rotation speeds of the first water pump, the second water pump, the third water pump, and the fourth water pump, respectively, N c is the compressor rotation speed, k1 is the working state of the eight-way valve, k2 and k3 are the working states of the first three-way valve and the second three-way valve, respectively, SOC t is the actual SOC value; in the model predictive control, the optimal control cost function of the energy-heat integrated system is: wherein, ξ fuel (t) represents the fuel consumption of the power system, E EMS (t) represents the electric energy consumption of the power system, E TMS (t) represents the total energy consumption of the heat management system working components, and κ1, κ2, and κ3 are the weights of the fuel consumption, the electric energy consumption, and the heat evaluation function score. Based on the implementation of the multi-power-source electric drive energy-heat integrated system, the multi-power-source electric drive energy-heat integrated system includes: wherein, is the predicted value of the objective optimization function at time k + j, u[k + i] is the control input at time k + i, Δu[k + i] is the control input increment at time k + i, N and N u is the number of training points selected from the sample data, Q is the weight of the objective optimization function, R u is the weight of the control input, R Δ is the weight of the control input increment.

2. The method of claim 1, wherein, an electric drive electric control loop, which is sequentially connected by a first water pump (2), an electric motor controller (3), an electric motor (4), a three-in-one (6), and an electric drive electric control radiator (7); a range extender loop, which is sequentially connected by a second water pump (8), a range extender (9), a first heat exchanger (10), a throttle valve (11), and a range extender unit radiator (12); a battery loop, which includes a third water pump (13), a first three-way valve (14), a cold air core (15), a second heat exchanger (16), and a battery pack (17), the third water pump (13) is connected to the cold air core (15) and the second heat exchanger (16) through the first three-way valve (14), and then connected to the battery pack (17); the battery pack (17) and the range extender (9) provide power for the electric motor controller (3); a heating and warming loop, which includes a PTC (18), a second three-way valve (19), a third heat exchanger (20), a warm air core (21), and a fourth water pump (22), the PTC (18) is connected to the third heat exchanger (20) and the warm air core (21) through the second three-way valve (19), and then connected to the fourth water pump (22); an air conditioning cooling and heat exchange loop, which is sequentially connected by a compressor (23), a condenser (24), a liquid storage tank (25), an electronic expansion valve (26), the second heat exchanger (16), and the first heat exchanger (10), the condenser (24) is connected to the third heat exchanger (20); ​ Eight-way valve (1), provided with working port a, working port b, working port c, working port d, working port e, working port f, working port g and working port h;The two ends of the electric drive electric control circuit are connected with working port a and b respectively, the two ends of the range extender circuit are connected with working port c and d respectively, the two ends of the battery circuit are connected with working port e and f respectively, and the two ends of the heating and warming circuit are connected with working port g and h respectively; The three-in-one (6) includes a charger, a distribution box and a DC / DC converter.

3. The method of claim 2, wherein, The electric drive electric control radiator (7) and the range extender unit radiator (12) are both provided with cooling fans.

4. The method of claim 2, wherein, The cold air core (15) and the warm air core (21) are both provided with air blowers.

5. The method of claim 2, wherein, The working modes of the energy-heat integrated system of the multi-power source electric drive include: the waste heat of the electric drive electric control circuit is used for battery heating, the waste heat of the electric drive electric control circuit is used for cabin heating, PTC is used for battery heating, PTC is used for cabin heating, each circuit is cooled by itself, the air conditioning cooling and heat exchange circuit is used for battery pack cooling and cabin cooling, the air conditioning cooling and heat exchange circuit is used for cabin dehumidification and battery pack cooling and cabin cooling, the waste heat of the engine is used for cabin heating, and the waste heat of the engine is used for battery heating.

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