Thermal management energy consumption coupling hybrid power tractor energy optimization method

Abstract

The invention belongs to the technical field of hybrid power vehicle energy management, and relates to a thermal management energy consumption coupling hybrid power tractor energy optimization method which considers interaction of a thermal management system and a driving system. Comprising the steps of constructing a hybrid tractor system model; establishing a hybrid power tractor power system thermal management cost model; on the basis of an equivalent consumption minimum strategy, under the constraint that boundary conditions are met, the influence of thermal management on performance at high temperature is comprehensively considered, and the operating states of a diesel engine and a motor are reasonably adjusted through optimization, so that equivalent fuel consumption is minimum under multi-objective optimization, and instantaneous optimal diesel engine and battery output power and thermal management power consumption are obtained; and based on the output result of the above steps, the thermal management cooling system and the power system are coupled through a logic interface, and the energy consumption required by battery cooling is transmitted to the cooling equipment.

Description

Technical Field

[0001] This invention belongs to the field of hybrid vehicle energy management technology, specifically relating to a thermal management energy consumption coupled hybrid tractor energy optimization method. Background Technology

[0002] With the rapid development of the automotive industry and the depletion of non-renewable energy sources, improving the energy efficiency of vehicles has become a primary goal in the automotive development stage. Whether it's a new energy vehicle or a traditional vehicle, the overall energy consumption of the vehicle has always been a crucial factor for manufacturers and users; therefore, reducing energy consumption is one of the long-term goals of the automotive industry.

[0003] The optimal operating temperature range for lithium-ion power batteries is between 15℃ and 35℃, with an allowable operating temperature range of 0℃ to 45℃. During the peak summer season, when tractors are busy in the fields, the surface temperature of the batteries can reach 60-80℃, and the core temperature of the cells can reach 95-105℃, far exceeding safety thresholds. If the operating temperature of the power battery exceeds this specific range, its performance will not only be affected but safety issues may also arise. To meet the heat dissipation requirements of power batteries, current hybrid tractor power battery cooling solutions mainly rely on liquid cooling. Given my country's vast territory, ambient temperatures ranging from -30℃ to 55℃ are becoming increasingly common for electric vehicles. To ensure that tractors can operate normally in any region and season in my country, the importance of thermal management systems is becoming increasingly prominent.

[0004] The operating conditions of the powertrain system guide the control methods of the thermal management system, and the combination of energy management and thermal management has always been a crucial support for reducing vehicle energy consumption. Vehicle energy consumption can be divided into two main categories: one is energy management that focuses more on vehicle dynamics, and the other is energy consumption optimization based on the thermal system. Existing research mainly focuses on either single energy management or thermal management areas, with relatively little research on the coupling between the two. For multi-objective optimization problems, the Equivalent Consumption Minimization Strategy (ECMS) is widely used in energy management.

[0005] In terms of thermal management, the drive system of hybrid electric vehicles is more complex than that of traditional vehicles and pure electric vehicles. The temperature of the three major components of the drive system—engine, motor, and power battery—directly affects the power characteristics of the entire vehicle. Under the constantly changing operating conditions of hybrid electric vehicles, adjusting the operation of each component within a suitable temperature range can not only ensure vehicle performance but also extend the service life of the components.

[0006] Due to their working environments (such as field operations and low-speed traction) and power characteristics, tractors suffer from insufficient forced convection cooling, and experience continuous high loads and concentrated heat generation. Tractors typically operate at speeds below 30 km / h, at which point the relative velocity between the vehicle and the air is extremely low, significantly different from that of cars, greatly reducing natural convection and cooling effects. Tractors often operate under continuous high loads with large load fluctuations, resulting in a heat generation rate far exceeding that of passenger cars under normal driving conditions. Cars, on the other hand, easily reach speeds of 60 km / h, significantly increasing the relative velocity between the vehicle and the air. This enhances the forced convection heat transfer effect of cooling components such as condensers and radiators, making cooling capacity highly dependent on speed and complex to control. This approach is not suitable for tractor operating conditions, but normalized algorithms for power battery cooling energy consumption and cooling time are more appropriate for tractor conditions. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention provides an energy optimization method for thermal management energy consumption coupled with hybrid power tractors suitable for high-temperature regions.

[0008] The objective of this invention is achieved through the following technical solution. According to this invention, a thermal management energy consumption coupling hybrid tractor energy optimization method is proposed. This method is based on a hybrid tractor energy management system composed of a diesel engine and a power battery or other energy source. The tractor has two drive systems: a diesel engine and an electric motor. The engine and electric motor output torque are output through a torque coupler, and it also has a PTO power output device. This method considers the impact of cooling power requirements, cooling time, and temperature on economic efficiency, and specifically includes the following steps:

[0009] S1: Construct a hybrid tractor system model, which includes a tractor terminal energy model, a power model, a powertrain heat generation model, and a tractor thermal management system cooling model. Step S1 includes the following sub-steps:

[0010] S11: Constructing a terminal energy model for hybrid tractors;

[0011] S12: Establish diesel engine power model, electric motor power model, and battery discharge model for a hybrid tractor power system.

[0012] S13: Construct a heat generation model for the diesel engine, lithium battery, and electric motor in the thermal management system of a hybrid tractor;

[0013] S14: Establish a refrigeration model for the thermal management system of a hybrid tractor;

[0014] S2: Establish a thermal management cost model for hybrid tractor power systems;

[0015] S3: Based on the strategy of minimizing equivalent consumption, the power consumption of electricity is converted into fuel consumption. Under the constraint of satisfying the boundary conditions, the operating state of the diesel engine and the electric motor is optimized to minimize the equivalent fuel consumption, thereby obtaining the instantaneous optimal output power of the diesel engine and battery and the thermal management power consumption.

[0016] S4: Based on the output of step S3, energy is allocated reasonably. Through the integrated architecture of thermal management and energy management bidirectional interaction, the thermal management cooling system and the hybrid power system are coupled through a logical interface, and the energy consumption required for battery cooling is transferred to the cooling equipment.

[0017] Furthermore, the construction of the model described in S11 is specifically as follows:

[0018] P req =P g +P PTO +P f +P p +p w

[0019]

[0020] P req =η e η t1 P ereq +η m ηt2P mreq

[0021] P req The remote power output of the hybrid tractor, P g Tillage power (maximum for plowing), P PTO Power output, P f P p p w These represent rolling resistance power, slope resistance power, and wading power, respectively; Z represents the number of plowshares, b... i Width of a single plowshare, h k Tillage depth, k (soil specific resistance), unit N / cm 2 m is the tractor's operating mass, in kg; f is the rolling resistance coefficient; α is the slope; ρ h Water density, b t Total width of tires and plow, h h Water depth; v (tractor operating speed), unit: km / h; η (trailer speed) e For engine efficiency, η m For motor efficiency, η t1 Engine power coupling efficiency, η t2 Coupling efficiency of motor power. P ereq P mreq These are the engine power requirement and the electric motor power requirement, respectively.

[0022] Furthermore, the model construction described in step S12 specifically involves:

[0023] Establishing a diesel engine power model: The operating temperature of a tractor operating at high temperatures and with high power has a significant impact on diesel engine efficiency. Instantaneous fuel consumption is corrected using a temperature function coefficient.

[0024] By obtaining the universal characteristic diagram of the diesel engine and performing interpolation calculations, the average fuel consumption rate at the corresponding operating point of the engine can be obtained. Then, the formula can be used to calculate the fuel consumption rate. To obtain the engine fuel consumption. Fuel consumption of the engine per unit time; b is the engine fuel consumption rate, in g / (kWh); n e Engine speed, in rpm; T d Engine torque, N·m;

[0025]

[0026] This reflects the actual fuel economy of the engine at different temperatures, providing a quantitative method for calculating the impact of temperature on efficiency in energy management strategies. The correction coefficient only considers temperature; after fitting, both ancd and α are constants, hence the expression in parentheses represents a function of temperature. Based on the instantaneous fuel consumption of the engine under optimal calibration conditions, T e Here, represents the engine coolant temperature, and 'e' is the temperature correction factor for the diesel engine's instantaneous fuel consumption, with an optimal value of 1. The value of 'e' for the engine is determined by least-squares fitting of bench test data at different temperatures:

[0027]

[0028] a = -0.0083 [℃] -1 b = 1.666, c = -0.005 [℃] -1 d = 1.4, Te L =20℃,Te H =100℃, Low temperature threshold, The high temperature threshold, This is the optimal point temperature value;

[0029] Establish a motor power model: Obtain the relationship between motor system efficiency and torque and speed using bench test data of motor efficiency;

[0030] Battery discharge model: The lithium-ion battery model is based on the internal resistance model (Rint model) to simulate the working characteristics of the battery.

[0031] Furthermore, the model construction described in step S13 includes:

[0032] Diesel engine heat generation model:

[0033] Q eheat =Q e -P ereq

[0034]

[0035] Q e Total energy released by fuel combustion, expressed in kJ / s, Q. eheat The heat output of a diesel engine per unit time, i.e., the heat that the cooling system needs to remove, is denoted by Q. l Diesel fuel has a low calorific value, measured in kJ / kg.

[0036] Bernadi model of lithium battery heat generation:

[0037] During operation, the heat sources of lithium-ion power batteries mainly include electrochemical reaction heat and polarization heat. The electrochemical reaction heat of lithium-ion batteries is relatively low and can be ignored in practical calculations. The Bernadi heat generation model, which combines polarization heat and entropy heat, can be used for power batteries.

[0038]

[0039] Q bat Instantaneous heat generation rate of the battery; I: battery charge / discharge current (A); U0: battery open-circuit voltage (V); U: battery operating voltage (V); R: battery internal resistance. Entropy heat coefficient;

[0040] The motor heat generation model includes:

[0041] Q motor =P mreq (1-η m )

[0042] Q motor P is the instantaneous heat generation rate of the motor. mreq Motor power requirement, η m This refers to the motor efficiency.

[0043] Further, step S14 involves modeling the refrigeration model, specifically including:

[0044] The cooling subsystem uses both liquid cooling and air cooling. The liquid cooling and air cooling are forced convection heat dissipation. The cooling capacity of the lithium battery and diesel engine is controlled independently. The air cooling uses a fan. For tractor speeds below 30km / h, natural convection is not considered.

[0045] The air velocity passing through the radiator is composed of the wind speed at the radiator inlet and the wind speed increased when the fan is working. However, since the tractor travels at speeds below 30 km / h, the wind speed of natural convection through the radiator is ignored, and only the fan speed is considered.

[0046]

[0047] For airflow, D f C is the equivalent diameter of the fan. f N is the flow coefficient. f P is the fan speed. f k represents the power consumption of the heatsink. f Here, c is the equivalent energy consumption parameter of the fan, and ρ is the heat capacity coefficient. air air density, Q f The amount of heat dissipated by the fan in time t, expressed in kJ. Heat dissipation per unit time, in kW; ΔT is the temperature difference between the air inlet and outlet of the radiator, in °C.

[0048] Modeling of the cooling pump cooling subsystem includes:

[0049] Simulation Modeling: As the main energy-consuming component in the thermal management system, the cooling pump's pressure difference, composed of pipe resistance and pressure drop of the heat dissipation module, is a direct parameter determining its power consumption. By setting the cooling pump's speed-flow-pressure difference curve, data graphs of the cooling pump in actual operation were obtained. The model uses data interpolation to obtain the inlet and outlet pressure differences and flow rates at different speeds.

[0050]

[0051] P m The unit is the cooling pump power (W); Q is the cooling pump flow rate (L / min); Δp is the inlet / outlet pressure difference (bar); f e For cooling pump efficiency;

[0052] Numerical modeling:

[0053]

[0054] The coolant flow rate is determined by the coolant pump speed. The coolant circulation flow rate can be calculated based on the required heat dissipation. Cooling water circulation flow rate, Q w Heat dissipation W, Q v Coolant volume flow rate (m) 3 / s, Δt w p is the maximum temperature rise of the coolant. w c is the density of the coolant. w P is the specific heat capacity of the coolant. mThe output power of the cooling pump, ρ w The density of the coolant delivered to the cooling pump, g is the acceleration due to gravity, H is the head of the cooling pump, and η is the pump head. p This refers to the mechanical efficiency of the cooling pump.

[0055] Furthermore, the cost model for the thermal management system of the hybrid tractor power system in step S2 is as follows:

[0056] The thermal management system cost model includes engine cooling energy consumption, motor cooling energy consumption, battery cooling energy consumption, and equivalent power loss due to battery cooling time. Considering the high temperature sensitivity of the power battery, the battery thermal management energy consumption and cooling time cost (equivalent power loss due to battery cooling time) are unified into an instantaneous cost rate in the power dimension using a normalization algorithm, and the total cost is accumulated through time integration. As the rotational speed increases, the shaft power increases significantly according to the characteristic diagram of the circulating cooling pump. Within a relatively reasonable cooling time, there will be situations with slower cooling and lower energy consumption at low speeds and faster cooling and higher energy consumption at high speeds. Within the acceptable cooling time and energy consumption range, various control strategies are adopted. The weights of cooling time and energy consumption are dynamically adjusted according to real-time operating conditions (such as ambient temperature, component temperature, battery SOC, etc.) so that the cost function can adapt to the priority requirements of different scenarios.

[0057] The cost of cooling time includes the battery's high requirements for operating temperature and the performance loss (efficiency), lifespan loss, and decreased charge retention capacity caused by the deviation between component temperature and target temperature. The principle and implementation steps for converting it into a unified equivalent power metric are as follows:

[0058] The cumulative cost expression is:

[0059]

[0060] m inst Instantaneous cooling time degradation, r T Cooling rate, r T,max Fastest cooling rate, r T,min Slowest cooling rate; P0 reference power, in kW; q max q min For the extreme value of total energy consumption, t max t min This represents the extreme value of the total time; when r T Approaching r T,max The cooling rate is fast, m inst ≈0, meaning the time penalty is small; n inst P represents the instantaneous energy consumption degradation degree. max P min For minimum and maximum cooling power; when P batcool =P min Lowest energy consumption, ninst =0, meaning the energy penalty is small; P bat,cool (t) The actual power consumed by the battery cooling system at time t, in kW; a: Time degradation weighting coefficient (0≤a≤1), the larger the value, the heavier the penalty for slow cooling; b: Energy consumption degradation weighting coefficient (0≤b≤1), the larger the value, the heavier the penalty for high energy consumption; t0 is the initial time, t f At the terminal time, H(P) ereq ,t) represents the time interval [t0, t f The cumulative thermal management energy cost within [ ], α, β(t) are the diesel engine cooling cost coefficient and the electric motor cooling cost coefficient, respectively; γ(t) is the battery cost coefficient; P mreq (t) Current motor power demand

[0061] An a and b allocation strategy based on SOC and battery temperature is adopted for dynamic allocation of time and energy consumption. The core objective is to balance load demand, SOC and battery temperature efficiency loss and lifespan.

[0062] The following is the specific design plan:

[0063] Condition 1: SOC is between 50% and 100% and battery temperature T is between 35°C. Time degradation weighting coefficient a = 0 and energy consumption degradation weighting coefficient b = 0. The battery's additional penalty disappears, and power consumption is prioritized.

[0064] Operating Condition 2: SOC is between 50% and 100% and battery temperature T is ≥ 35℃. The time degradation weighting coefficient a = 0.5 - (0.05(T-35)) and the energy consumption degradation weighting coefficient b = 1 - a. That is, for every 1℃ increase in battery temperature T, a decreases by 0.05.

[0065] Operating Condition 3: SOC is between 50% and 100% and battery temperature T is greater than or equal to 50°C. Time degradation weighting coefficient a = 0, energy consumption degradation weighting coefficient b = 1, and the thermal management system operates at maximum power.

[0066] Operating Condition 4: SOC≤50%, time degradation weighting coefficient a=0.5+(0.05(SOC-50%) / 100%), energy consumption degradation weighting coefficient b=1-a, that is, for every 1% decrease in SOC, a increases by 0.05.

[0067] Operating Condition 5: SOC < 30%, time degradation weighting coefficient a = 1, energy consumption degradation weighting coefficient b = 0. The system prioritizes energy saving.

[0068] Furthermore, the instantaneous optimization control strategy based on the equivalent cost minimization strategy in step S3 is specifically as follows:

[0069] Under the constraint of satisfying the boundary conditions, the equivalent fuel consumption is minimized by optimizing the reasonable allocation of the operating state between the diesel engine and the electric motor, and the instantaneous optimal diesel engine and battery output power and thermal management power consumption (mainly the power consumption caused by the cooling pump speed) are obtained.

[0070] In high-temperature environments, the energy consumption of the cooling system (such as fans and liquid cooling pumps) may account for 10%-20% of the total energy consumption. If the energy management system ignores this energy consumption, the planned energy allocation will not reserve the cooling equipment demand, resulting in insufficient actual power. The main power-consuming components in the thermal management cooling system, such as fans and cooling pumps, can reflect the overall energy consumption of the vehicle. Through the control and optimization of the structure and input parameters of the vehicle's powertrain and thermal management cooling system, the ultimate goal is to reduce energy consumption and improve efficiency. The performance index function based on the strategy of minimizing equivalent consumption is...

[0071]

[0072] The Hamiltonian function expression for this optimization problem is as follows:

[0073]

[0074] Solving this objective function can be seen as a specific application of the PMP principle. Based on real-time feedback from battery SOC and temperature, the equivalence factor can be adjusted online to obtain a variable equivalence factor related to real-time operating conditions.

[0075] To improve the tracking performance of the equivalent factor to a greater extent and make the reference value and the actual change trend of the variable equivalent factor the same, a weighted moving average method is used to adjust the reference value of the equivalent factor so that the obtained variable equivalent factor has a higher adaptability to the working conditions.

[0076] The equivalent factor expression is:

[0077] s ref，k+1 = (1-z)·s ref，k +z·s k

[0078]

[0079] △=k SOC ·Δ SOC +k T ·△ T

[0080]

[0081] The operational capabilities of each component are limited by real-world conditions, and the constraints that need to be met include:

[0082] The cooling equipment in the thermal management system is all powered by batteries.

[0083]

[0084] P elec P represents the electric power of the motor. mec Motor mechanical power; Q c (t) Equivalent fuel consumption, j e Oil price, unit: yuan / L; j m Electricity price, unit: yuan / kW·h; η chg η dis These represent the charge and discharge efficiencies of the battery; they are related to the battery properties; where t = k·VT, k = 1, 2, ..., S. ref，k S ref，k+1 Here are the equivalent factor reference values ​​calculated for the k-th and (k+1)-th iterations, z is the weight value, and s k+1 Let dSOC be the equivalent factor calculated in the (k+1)th iteration, VT be the sampling period, dSOC be the allowable range of battery SOC variation, dT be the allowable range of battery temperature variation, and l1 and l2 be adjustment parameters. By adjusting these two values, the shape of the penalty function can be controlled, thereby controlling the response speed of the penalty function to changes in battery SOC and battery temperature. Using a tangent function for battery SOC penalty function allows for a rapid response to SOC changes, effectively controlling SOC and battery temperature within a reasonable range. It also enables online adjustment of the equivalent factor, effectively reducing its sensitivity to operating conditions. in，ma x and P out，max P provides the maximum charge and discharge power for the battery Bat (t) Current charging / discharging power; SOC min The set lower limit for battery SOC; SOC max The upper limit of battery SOC is set, and SOC(t) is the SOC value at the current time; P M,max P is the maximum power of the drive motor. M (t) Current power of the drive motor; P pto,max Maximum power of tractor power output motor, P pto (t) Current power of the power output motor; P ereq，max The maximum power of the diesel engine; x = p1, p2, p3 are the speeds of the cooling water pumps in the three circuits, respectively. e，min and n e,max The minimum and maximum stable speeds of the diesel engine are set; n M,max and n pto,max These are the speed limits for the tractor drive motor and the power take-off motor, respectively. e，min and T e，max For diesel engine temperature limiting conditions; T min and T maxPermissible temperature variation range of the battery;

[0085] Furthermore, step S4, based on the output of step S3, rationally allocates energy and, through the integrated architecture of thermal management and energy management bidirectional interaction, couples the thermal management cooling system with the hybrid power system via a logical interface (CAN bus data interaction), transmitting the energy consumption required for battery cooling to the corresponding cooling equipment.

[0086] As mentioned above, ignoring natural convection cooling, under the default full-power radiator operation, the cooling capacity of the battery cooling system is only related to the power consumption of the cooling pump. Therefore, the cooling capacity under this temperature and operating condition can be obtained through the cooling cost factor, achieving bidirectional coupling. The specific method of autoregressive motion control is: P m-b =γ(P bat，cool -P f1 )+k P (T ref -T(t)), the first part of which determines the cooling demand power consumption through the cooling cost factor in the algorithm, and the second part is used to stabilize the water pump energy output, while avoiding thermal runaway and eliminating errors, controlling the actual battery temperature close to the reference temperature. This method reasonably avoids drastic fluctuations in water pump speed and does not cause frequent jumps in the equivalent factor due to battery temperature. Similarly, the cooling circuits of the diesel engine and electric motor adopt the same control method to achieve energy management. P m-b P is the power of the cooling water pump in the battery cooling circuit. f1 This represents the maximum power output of the battery cooling circuit radiator. P This is the temperature difference coefficient.

[0087] Furthermore, the corresponding output flow rate values ​​are determined based on the circuit temperatures of the thermal management cooling circuits corresponding to the engine, motor, and battery.

[0088] Furthermore, the cooling circuit also includes an air conditioning heat exchanger model. The main function of the compressor is to maintain the normal operation of the air conditioning system and provide the corresponding flow rate. The flow rate control can be based on simulation analysis, or a simple flow rate calculation method based on efficiency calculation can be directly added to the cooling model.

[0089] Compared with the prior art, the advantages of the present invention are:

[0090] 1. This invention discloses an energy optimization method for a hybrid tractor with thermal management energy consumption coupling. In the prior art, under high-temperature and high-power operating conditions, the energy consumption of the cooling system (such as fan and liquid cooling pump) may account for 10%-20% of the total energy consumption. No energy consumption space is reserved for the cooling system, and existing research mainly focuses on a single energy management or thermal management field, with relatively little research on the coupling between the two.

[0091] This method considers the interaction between the thermal management system and the drive system, taking into account the impact of energy consumption on the temperature of components affected by heat on the battery and diesel engine. Based on the adaptive equivalent fuel consumption minimization strategy of thermal management condition feedback, it improves the overall economy and thermal management effect of hybrid tractors by optimizing the power distribution and temperature control between the diesel engine and the battery.

[0092] 2. In the existing technology, the various related items (different components) involving temperature mostly adopt independent control mode, without considering the coupling relationship between the various related items (for example, the impact of changes in motor temperature and power on battery heat dissipation power demand and cooling time, which leads to the thermal management having the energy consumption optimization of a single component rather than the global optimization, and may even result in high energy consumption scenarios such as one component being overcooled while another component is too hot).

[0093] This invention employs a hierarchical collaborative design of temperature-related terms, locally active optimization of battery cooling time (used to determine battery temperature control power), and passive global optimization of battery SOC and temperature (the entire power consumption end). By constructing a time-varying reference value through weighted moving averages, the adjustment benchmark of the equivalent factor is bound to real-time operating conditions. Introducing the interval sensitivity of the tangent function, when the deviation approaches the boundary, the tangent function changes non-linearly and rapidly; when the deviation is small, the function changes smoothly, avoiding frequent adjustments and better reflecting the impact of battery SOC and temperature on the battery. A dynamic coupling model is established between various temperature-related terms (including temperature characteristics, performance loss due to cooling time, lifespan loss, and decrease in charge retention capacity, converted into a unified metric). This addresses the control deficiencies of individual temperature-related terms, achieving multi-objective energy consumption optimization and power control considering battery cooling time difference, SOC, and power system component temperatures, thereby improving energy efficiency.

[0094] 3. By employing an autoregressive motion control algorithm, the thermal management cooling system and the hybrid powertrain system are coupled through a logic interface (CAN bus data interaction), transmitting the energy consumption required for battery cooling to the corresponding cooling equipment. This temperature correction method reduces errors, thereby improving the accuracy and stability of thermal management control.

[0095] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the purpose, features and advantages of the present invention more obvious and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0096] Figure 1 This is a structural diagram of the energy and thermal management cooling system of a hybrid tractor power system provided in an embodiment of the present invention.

[0097] Figure 2This is a schematic diagram illustrating the operation of the ECMS-based energy management coupled hybrid tractor energy optimization method for high-temperature regions.

[0098] Figure 3 The graph shows the nonlinear characteristic s(t) of the weighted penalty function and the functional relationship between Δ and the change of the penalty function with the change of SOC under different weights.

[0099] Figure 4 This is a heat generation map of the motor obtained from the simulation.

[0100] Figure 5 This is a data graph showing the cooling pump in actual operation. Detailed Implementation

[0101] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0102] This invention discloses an energy optimization method for thermal management energy consumption coupling hybrid tractors applicable to high-temperature regions. This method is based on a series-parallel hybrid tractor energy management system composed of a diesel engine and a power battery or other energy source (such as a fuel cell). The overall vehicle thermal management power system cooling architecture includes an engine cooling subsystem (diesel engine cooling subsystem), an electric motor cooling subsystem, a lithium battery cooling subsystem, and an electronic component cooling subsystem. The overall architecture is as follows: Figure 1 As shown. The electronic components generate relatively little heat, so they are placed in the same cooling circuit as the motor. The PTO motor and the drive motor are connected in parallel to avoid interference, and then connected in series with the electronic components.

[0103] To simplify radiator modeling and considering current trends, the motor radiator fan, battery radiator fan, and engine radiator fan are arranged side-by-side horizontally on the chassis, sharing a common cooling fan. For example... Figure 2As shown, the corresponding cooling pump speed (flow rate) is determined based on the loop temperature of each thermal management cooling loop. The hybrid thermal management system also includes a vehicle controller and a temperature detection component, which is used to detect the temperature of each thermal management cooling loop. The vehicle controller is communicatively connected to the temperature detection component and the controller of the cooling devices (radiator fan, cooling pump). This tractor has two drive systems: a diesel engine and an electric motor. The output torque of the engine and the electric motor is transmitted to the input shaft of the transmission through a torque coupler. The transmission outputs power as the power input of the central drive unit and the PTO power output shaft, respectively. This method considers the impact of cooling power requirements, cooling time, and temperature on economy, and specifically includes the following steps:

[0104] S1: Construct a hybrid tractor system model, which includes a tractor terminal energy model, a power model, a powertrain cooling subsystem model, and a tractor thermal management system refrigeration model. Step S1 includes the following sub-steps:

[0105] S11: Constructing a terminal energy model for hybrid tractors;

[0106] S12: Establish diesel engine power model, electric motor power model, and battery discharge model for a hybrid tractor power system.

[0107] S13: Construct heat generation models for diesel engine, lithium battery, and electric motor in the thermal management system of a hybrid tractor.

[0108] S14: Establish a refrigeration model for the thermal management system of a hybrid tractor;

[0109] S2: Establish a thermal management cost model for hybrid tractor power systems;

[0110] S3: Based on the strategy of minimizing equivalent consumption, the power consumption of electricity is converted into fuel consumption. Under the constraint of satisfying the boundary conditions, the operating state of the diesel engine and the electric motor is optimized to minimize the equivalent fuel consumption, thereby obtaining the instantaneous optimal output power of the diesel engine and battery and the thermal management power consumption.

[0111] S4: Based on the output of step S3, energy is allocated reasonably. Through the integrated architecture of thermal management and energy management bidirectional interaction, the thermal management cooling system and the hybrid power system are coupled through a logical interface, and the energy consumption required for battery cooling is transferred to the cooling equipment.

[0112] The S11 model is constructed as follows:

[0113] P req =P g +P PTO +P f +P p +p w

[0114]

[0115] P req =η e η t1 P ereq +η m η t2 P mreq

[0116] P req The remote power output of the hybrid tractor, P g Tillage power (maximum for plowing), P PTO Power output, P f P p p w These represent rolling resistance power, slope resistance power, and wading power, respectively. Z represents the number of plowshares, and b... l Width of a single plowshare, h k Tillage depth, k (soil specific resistance), unit N / cm 2 m is the tractor's operating mass, in kg; f is the rolling resistance coefficient; α is the slope; ρ h Water density, b t Total width of tires and plow, h h Water depth, v (tractor operating speed), in km / h. η e For engine efficiency, η m For motor efficiency, η t1 Engine power coupling efficiency, η t2 Coupling efficiency of motor power. P ereq P mreq These are the engine power requirement and the electric motor power requirement, respectively.

[0117] The model construction described in step S12 is specifically as follows:

[0118] (1) Establishing a diesel engine power model: The operating temperature of a tractor operating at high temperature and high power has a significant impact on the efficiency of the diesel engine. Instantaneous fuel consumption is corrected using a temperature function coefficient.

[0119] By obtaining the universal characteristic diagram of the diesel engine and performing interpolation calculations, the average fuel consumption rate at the corresponding operating point of the engine can be obtained. Then, the formula can be used to calculate the fuel consumption rate. To obtain the engine fuel consumption. Fuel consumption of the engine per unit time; b is the engine fuel consumption rate, in g / (kWh); n e Engine speed, in rpm; T d Engine torque, N·m;

[0120]

[0121] in, Based on the instantaneous fuel consumption of the engine under optimal calibration conditions, T e Here, represents the engine coolant temperature, and 'e' is the temperature correction factor for the diesel engine's instantaneous fuel consumption, with an optimal value of 1. The value of 'e' for the engine is determined by least-squares fitting of bench test data at different temperatures:

[0122]

[0123] a = -0.0083 [℃] -1 b = 1.666, c = -0.005 [℃] -1 d = 1.4, Te L =20℃,Te H =100℃, Low temperature threshold, The high temperature threshold, This is the optimal temperature value.

[0124] (2) Establish motor power model: Obtain the relationship between motor system efficiency and torque and speed through the test data of motor efficiency bench.

[0125] The model construction described in step S13 includes:

[0126] (1) Diesel engine heat generation model

[0127] Q eheat =Q e -P ereq

[0128]

[0129] Q e The total energy released by fuel combustion, expressed in kJ / s. Q eheat The heat generated by a diesel engine per unit time is the heat that the cooling system needs to remove. Q l Diesel fuel has a low calorific value, measured in kJ / kg.

[0130] (2) Bernadi heat generation model for lithium batteries:

[0131] During operation, the heat sources of lithium-ion power batteries mainly include electrochemical reaction heat and polarization heat (ohmic polarization, concentration polarization, electrochemical polarization, etc.). Among these, the electrochemical reaction heat of lithium-ion batteries is relatively low and can be ignored in practical calculations. The Bernadi heat generation model, which combines polarization heat and entropy heat, can be used for power batteries.

[0132]

[0133] Q bat Instantaneous heat generation rate of the battery; I: battery charge / discharge current (A); U0: battery open-circuit voltage (V); U: battery operating voltage (V); R: battery internal resistance. Entropy heat coefficient.

[0134] (3) The heat generation model of the motor includes:

[0135] Q motor =P mreq (1-η m )

[0136] Q motor P is the instantaneous heat generation rate of the motor. mreq Motor power requirement, η m This refers to the motor efficiency.

[0137] Step S14 involves modeling the refrigeration model, specifically including:

[0138] The cooling subsystem uses both liquid cooling and air cooling. The liquid cooling and air cooling are forced convection heat dissipation. The cooling capacity of the lithium battery and diesel engine is controlled independently. The air cooling uses a fan. For tractor speeds below 30km / h, natural convection is not considered.

[0139] The air velocity passing through the radiator consists of the wind speed at the radiator inlet and the increased wind speed when the fan is working. However, since the tractor travels at speeds below 30 km / h, the natural convection wind speed at the radiator inlet is ignored, and only the wind speed of the electric fan is considered.

[0140]

[0141] For airflow, D f C is the equivalent diameter of the fan. f N is the flow coefficient. f P is the fan speed. f k represents the power consumption of the heatsink. f ρ represents the equivalent energy consumption parameter of the fan. c is the heat capacity coefficient. air Air density (varies with temperature and altitude; 1.225 kg / m³ at normal temperature and pressure) 3 ), Q f The amount of heat dissipated by the fan in time t, measured in kJ. Heat dissipation per unit time, in kW; ΔT is the temperature difference between the air inlet and outlet of the radiator, in °C.

[0142] Modeling of the cooling pump cooling subsystem includes:

[0143] Simulation Modeling: As a major component consuming electrical energy in the thermal system, the cooling pump's pressure difference, composed of pipe resistance and pressure drop of the heat dissipation module, is a direct parameter determining its power consumption. By setting the cooling pump's speed-flow-pressure difference curve, data graphs of the cooling pump in actual operation were obtained. In the model, inlet and outlet pressure differences and flow rates at different speeds were obtained through data interpolation.

[0144]

[0145] P m The unit is the cooling pump power (W); Q is the cooling pump flow rate (L / min); Δp is the inlet / outlet pressure difference (bar); f e For cooling pump efficiency.

[0146] Numerical modeling:

[0147]

[0148] The coolant flow rate is determined by the coolant pump speed. The coolant circulation flow rate can be calculated based on the required heat dissipation. Q is the cooling water circulation flow rate. w Heat dissipation W, Q v Coolant volume flow rate (m) 3 / s, △t w p is the maximum temperature rise of the coolant. w c is the density of the coolant. w P represents the specific heat capacity of the coolant. m The output power of the cooling pump, ρ w The density of the coolant delivered to the cooling pump, g is the acceleration due to gravity, H is the head of the cooling pump, and η is the pump head. p This refers to the mechanical efficiency of the cooling pump.

[0149] The cost model for the thermal management system of the hybrid tractor power system described in step S2 is as follows:

[0150] The thermal management system cost model includes engine cooling energy consumption, motor cooling energy consumption, battery cooling energy consumption, and equivalent power loss due to battery cooling time. Considering the high temperature sensitivity of the power battery, the battery thermal management energy consumption and cooling time cost (equivalent power loss due to battery cooling time) are unified into an instantaneous cost rate in the power dimension using a normalization algorithm, and the total cost is accumulated through time integration. As the rotational speed increases, the shaft power increases significantly according to the characteristic diagram of the circulating cooling pump. Within a relatively reasonable cooling time, there will be situations with slower cooling and lower energy consumption at low speeds and faster cooling and higher energy consumption at high speeds. Within the acceptable cooling time and energy consumption range, various control strategies are adopted. The weights of cooling time and energy consumption are dynamically adjusted according to real-time operating conditions (such as ambient temperature, component temperature, battery SOC, etc.) so that the cost function can adapt to the priority requirements of different scenarios.

[0151] The cost of cooling time includes the battery's high requirements for operating temperature and the performance loss (efficiency), lifespan loss, and decreased charge retention capacity caused by the deviation between component temperature and target temperature. The principle and implementation steps for converting it into a unified equivalent power metric are as follows:

[0152] The cumulative cost expression is:

[0153]

[0154] m inst Instantaneous cooling time degradation, r T Cooling rate, r T,max Fastest cooling rate, r T，min Slowest cooling rate; P0 reference power, in kW; q max q min For the extreme value of total energy consumption, t max t min This represents the extreme value of the total time; when r T Approaching r T,max The cooling rate is fast, m inst ≈0, meaning the time penalty is small; n inst P represents the instantaneous energy consumption degradation degree. max P min For minimum and maximum cooling power; when P batcool =P min Lowest energy consumption, n inst =0, meaning the energy penalty is small; P bat，cool (t) The actual power consumed by the battery cooling system at time t, in kW; a: Time degradation weighting coefficient (0≤a≤1), the larger the value, the heavier the penalty for slow cooling; b: Energy consumption degradation weighting coefficient (0≤b≤1), the larger the value, the heavier the penalty for high energy consumption; t0 is the initial time, t f At the terminal time, H(P)ereq ,t) represents the time interval [t0, t f The cumulative thermal management energy cost within [ ], α, β(t) are the diesel engine cooling cost coefficient and the electric motor cooling cost coefficient, respectively; γ(t) is the battery cost coefficient; P mreq (t) The power demanded by the motor at the current moment.

[0155] An a and b allocation strategy based on SOC and battery temperature is adopted for dynamic allocation of time and energy consumption. The core objective is to balance load demand, SOC and battery temperature efficiency loss and lifespan.

[0156] The following is the specific design plan:

[0157] Condition 1: SOC is between 50% and 100% and battery temperature T is between 35°C. Time degradation weighting coefficient a = 0 and energy consumption degradation weighting coefficient b = 0. The battery's additional penalty disappears, and power consumption is prioritized.

[0158] Operating Condition 2: SOC is between 50% and 100% and battery temperature T is ≥ 35℃. The time degradation weighting coefficient a = 0.5 - (0.05(T-35)) and the energy consumption degradation weighting coefficient b = 1 - a. That is, for every 1℃ increase in battery temperature T, a decreases by 0.05.

[0159] Operating Condition 3: SOC is between 50% and 100% and battery temperature T is greater than or equal to 50°C. Time degradation weighting coefficient a = 0, energy consumption degradation weighting coefficient b = 1, and the thermal management system operates at maximum power.

[0160] Operating Condition 4: SOC≤50%, time degradation weighting coefficient a=0.5+(0.05(SOC-50%) / 100%), energy consumption degradation weighting coefficient b=1-a, that is, for every 1% decrease in SOC, a increases by 0.05.

[0161] Operating Condition 5: SOC < 30%, time degradation weighting coefficient a = 1, energy consumption degradation weighting coefficient b = 0. The system prioritizes energy saving.

[0162] The instantaneous optimization control strategy based on the equivalent cost minimization strategy in step S3 is as follows:

[0163] Under the constraints of the boundary conditions, by optimizing the reasonable allocation of the operating states between the diesel engine and the electric motor to minimize the equivalent fuel consumption, the instantaneous optimal output power of the diesel engine and battery and the thermal management power consumption (mainly the power consumption caused by the water pump speed) are obtained.

[0164] In high-temperature environments, the energy consumption of the cooling system (such as fans and cooling pumps) may account for 10%-20% of the total energy consumption. If the energy management system ignores this energy consumption, the planned energy allocation will not reserve the cooling equipment demand, resulting in insufficient actual power. The main power-consuming components in the thermal management cooling system, such as fans and cooling pumps, can reflect the overall energy consumption of the vehicle. Through the control and optimization of the structure and input parameters of the vehicle's powertrain and thermal management cooling system, the ultimate goal is to reduce energy consumption and improve efficiency. The performance index function based on the strategy of minimizing equivalent energy consumption is...

[0165]

[0166] The Hamiltonian function expression for this optimization problem is as follows:

[0167]

[0168]

[0169] Solving this objective function can be seen as a specific application of the PMP principle. Based on real-time feedback from battery SOC and temperature, the equivalence factor can be adjusted online to obtain a variable equivalence factor related to real-time operating conditions.

[0170] To improve the tracking performance of the equivalent factor to a greater extent and make the reference value and the actual change trend of the variable equivalent factor the same, a weighted moving average method is used to adjust the reference value of the equivalent factor so that the obtained variable equivalent factor has a higher adaptability to the working conditions.

[0171] The equivalent factor expression is:

[0172] s ref，k+1 = (1-z)·s ref，k +z·s k

[0173]

[0174] △=k SOC ·Δ SOC +k T ·△ T

[0175]

[0176] The operational capabilities of each component are limited by real-world conditions, and the constraints that need to be met include:

[0177] The cooling equipment in the thermal management system is all powered by batteries.

[0178]

[0179] Pelec P represents the electric power of the motor. mec Motor mechanical power; Q c (t) Equivalent fuel consumption, j e Oil price, unit: yuan / L; j m Electricity price, unit: yuan / kW·h; η chg η dis These represent the charge and discharge efficiencies of the battery; they are related to the battery properties; where t = k·VT, k = 1, 2, ..., S. ref，k S ref，k+1 Here are the equivalent factor reference values ​​calculated for the k-th and (k+1)-th iterations, z is the weight value, and s k+1 Let dSOC be the equivalent factor calculated in the (k+1)th iteration, VT be the sampling period, dSOC be the allowable range of battery SOC variation, dT be the allowable range of battery temperature variation, and l1 and l2 be adjustment parameters. By adjusting these two values, the shape of the penalty function can be controlled, thereby controlling the response speed of the penalty function to changes in battery SOC and battery temperature. Using a tangent function for battery SOC penalty function allows for a rapid response to SOC changes, effectively controlling SOC and battery temperature within a reasonable range. It also enables online adjustment of the equivalent factor, effectively reducing its sensitivity to operating conditions. in，max and P out，max P provides the maximum charge and discharge power for the battery Bat (t) Current charging / discharging power; SOC min The set lower limit for battery SOC; SOC max The upper limit of battery SOC is set, and SOC(t) is the SOC value at the current time; P M，max P is the maximum power of the drive motor. M (t) Current power of the drive motor; P pto,max Maximum power of tractor power output motor, P pto (t) Current power of the power output motor; P ereq，max The maximum power of the diesel engine; x = p1, p2, p3 are the speeds of the cooling water pumps in the three circuits, respectively. e，min and n e,max The minimum and maximum stable speeds of the diesel engine are set; n M,max and n pto,max These are the speed limits for the tractor drive motor and the power take-off motor, respectively. e，min and T e，max For diesel engine temperature limiting conditions; T min and T max Allowable temperature variation range for the battery.

[0180] In patent CN119447603A, a method for energy management of a diesel-electric hybrid power system under low-temperature conditions, the reference value is only defined by the operating condition and is fixed. This results in weak adaptability when the deviation is small. This invention constructs a time-varying reference value using a weighted moving average, binding the adjustment benchmark of the equivalent factor to the real-time operating condition, thus improving the strategy's operating condition tracking. Furthermore, linear response leads to over-response when the deviation is large. This invention introduces the interval sensitivity characteristic of the tangent function. When the deviation approaches the boundary, the tangent function changes non-linearly and rapidly; when the deviation is small, the function changes smoothly, avoiding frequent adjustments. This better reflects the influence of battery SOC and temperature on the battery, while balancing response speed and stability.

[0181] Step S4, based on the output of step S3, rationally allocates energy and, through the integrated architecture of thermal management and energy management bidirectional interaction, couples the thermal management cooling system with the hybrid power system via a logical interface (CAN bus data interaction), transmitting the energy consumption required for battery cooling to the corresponding cooling equipment.

[0182] As mentioned above, ignoring natural convection cooling, under the default full-power radiator operation, the battery cooling system's cooling capacity is only related to the cooling pump's power consumption. Therefore, the cooling capacity under this temperature and operating condition can be obtained through the cooling cost factor, achieving bidirectional coupling. The specific method of autoregressive motion control is: P m-b =γ(P bat，cool -P f1 )+k P (T ref -T(t)), the first part of which determines the cooling demand power consumption through the cooling cost factor in the algorithm, and the second part is used to stabilize the water pump energy output, while avoiding thermal runaway and eliminating errors, controlling the actual battery temperature close to the reference temperature. This method reasonably avoids drastic fluctuations in water pump speed and does not cause frequent jumps in the equivalent factor due to battery temperature. Similarly, the cooling circuits of the diesel engine and electric motor adopt the same control method to achieve energy management. P m-b P is the power of the cooling water pump in the battery cooling circuit. f1 This represents the maximum power output of the battery cooling circuit radiator. P This is the temperature difference coefficient.

[0183] The corresponding output flow rate value is determined based on the loop temperature of each thermal management cooling loop of the engine, motor, and battery.

[0184] The cooling circuit also includes an air conditioning heat exchanger model. The compressor's main function is to maintain the normal operation of the air conditioning system and provide the corresponding flow rate. Flow rate control can be based on simulation analysis, or a simpler flow rate calculation method based on efficiency calculation can be directly added to the cooling model.

Claims

1. A method for optimizing the energy consumption of a thermal management-coupled hybrid tractor, characterized in that: Includes the following steps: S1: Construct a hybrid tractor system model, which includes a tractor terminal energy model, a power model, a powertrain heat generation model, and a tractor thermal management system cooling model. Step S1 includes the following sub-steps: S11: Constructing a terminal energy model for hybrid tractors; S12: Establish diesel engine power model, electric motor power model, and battery discharge model for the hybrid tractor power system; S13: Construct a heat generation model for the diesel engine, lithium battery, and electric motor in the thermal management system of a hybrid tractor; S14: Establish a refrigeration model for the thermal management system of a hybrid tractor; S2: Establish a thermal management cost model for hybrid tractor power systems; S3: Based on the strategy of minimizing equivalent consumption, the power consumption is converted into fuel consumption. Under the constraint of satisfying the boundary conditions, the operating state of the diesel engine and the electric motor is optimized to minimize the equivalent fuel consumption, thereby obtaining the instantaneous optimal output power of the diesel engine and battery and the thermal management power consumption. S4: Based on the output of step S3, energy is allocated reasonably. Through the integrated architecture of thermal management and energy management bidirectional interaction, the thermal management cooling system and the hybrid power system are coupled through a logical interface, and the energy consumption required for battery cooling is transferred to the cooling equipment.

2. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: The model described in S11 is constructed as follows: P req =P g +P PTO +P f +P p +p w P req =the e or t1 P ereq +n m or t2 P mreq P req The remote power output of the hybrid tractor, P g Tillage power (maximum for plowing), P PTO Power output, P f P p p w These represent rolling resistance power, slope resistance power, and wading power, respectively; Z represents the number of plowshares, b... l Width of a single plowshare, h k Tillage depth, k (soil specific resistance), unit N / cm 2 m is the tractor's operating mass, in kg; f is the rolling resistance coefficient; α is the slope; ρ h Water density, b t Total width of tires and plow, h h Water depth; v (tractor operating speed), unit: km / h; η (trailer speed) e For engine efficiency, η m For motor efficiency, η t1 Engine power coupling efficiency, η t2 The coupling efficiency of motor power, P ereq P mreq These are the engine power requirement and the electric motor power requirement, respectively.

3. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: The model construction described in step S12 is specifically as follows: Establish a diesel engine power model: Correct instantaneous fuel consumption using temperature function coefficients. By obtaining the universal characteristic diagram of the diesel engine and performing interpolation calculations, the average fuel consumption rate at the corresponding operating point of the engine can be obtained. Then, the formula can be used to calculate the fuel consumption rate. To obtain the engine fuel consumption. Engine fuel consumption per unit time; b is engine fuel consumption rate, in g / (kWh); n e Engine speed, measured in rpm; T d Engine torque, N·m; in, Based on the instantaneous fuel consumption of the engine under optimal calibration conditions, T e Here, represents the engine coolant temperature, and 'e' is the temperature correction factor for the diesel engine's instantaneous fuel consumption, with an optimal value of 1. The value of 'e' for the engine is determined by least-squares fitting of bench test data at different temperatures: a = -0.0083 [℃] -1 b = 1.666, c = -0.005 [℃] -1 d = 1.4, Te L =20℃,Te H =100℃, , Low temperature threshold The high temperature threshold, This is the optimal point temperature value; Establish a motor power model: Obtain the relationship between motor system efficiency and torque and speed using bench test data of motor efficiency; Battery discharge model: The lithium-ion battery model is based on the internal resistance model to simulate the working characteristics of the battery.

4. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: The model construction described in step S13 includes: Diesel engine heat generation model: Q eheat =Q e -P ereq Q e Total energy released by fuel combustion, expressed in kJ / s, Q. eheat The heat output of a diesel engine per unit time, i.e., the heat that the cooling system needs to remove, is denoted by Q. l Diesel fuel has a low calorific value, measured in kJ / kg. Bernadi model of lithium battery heat generation: During operation, the heat sources of lithium-ion power batteries include electrochemical reaction heat and polarization heat. The electrochemical reaction heat of lithium-ion batteries is relatively low and is negligible in practical calculations. The Bernadi heat generation model, which combines polarization heat and entropy heat, can be used for power batteries. Q bat Instantaneous heat generation rate of the battery; I (battery charge / discharge current), in A; U0 (battery open-circuit voltage), in V; U (battery operating voltage), in V; R (battery internal resistance). Entropy heat coefficient; Electric motor heat generation model: Q motor =P mreq (1-η m ). Q motor P is the instantaneous heat generation rate of the motor. mreq Motor power requirement, η m For motor efficiency.

5. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: Step S14 involves modeling the refrigeration model, specifically including: The cooling system uses both liquid cooling and air cooling. The liquid cooling and air cooling are forced convection heat dissipation. The cooling capacity of the lithium battery and diesel engine is controlled independently. The air cooling capacity is controlled by the fan speed. The tractor speed is below 30km / h, so natural convection is not considered, only the fan speed is considered. For airflow, D f C is the equivalent diameter of the fan. f N is the flow coefficient. f P is the fan speed. f k represents the power consumption of the heatsink. f Here, c is the equivalent energy consumption parameter of the fan, and ρ is the heat capacity coefficient. air air density, Q f The amount of heat dissipated by the fan in time t, expressed in kJ. Heat dissipation per unit time, in kW; ΔT is the temperature difference between the air inlet and outlet of the radiator, in °C. Cooling pump refrigeration modeling includes: Simulation modeling: By setting the speed-flow-pressure difference curve of the cooling pump, data graphs of the cooling pump in actual operation were obtained. The model used data interpolation to obtain the inlet and outlet pressure difference and flow rate at different speeds. Pm is the cooling pump power, in W; Q is the cooling pump flow rate, in L / min; Δp is the inlet and outlet pressure difference, in bar; f e For cooling pump efficiency; Numerical modeling: The coolant flow rate is determined by the coolant pump speed. The coolant circulation flow rate can be calculated based on the required heat dissipation. Cooling water circulation flow rate, Q w Heat dissipation W, Q v Coolant volume flow rate (m) 3 / s, Δt w For the maximum temperature rise of the coolant, ρ w c is the density of the coolant. w P is the specific heat capacity of the coolant. m The output power of the cooling pump, ρ w The density of the coolant delivered to the cooling pump, g is the acceleration due to gravity, H is the head of the cooling pump, and η is the pump head. p This refers to the mechanical efficiency of the cooling pump.

6. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: The cost model for the thermal management system of the hybrid tractor power system in step S2 is as follows: The thermal management system cost model includes engine cooling energy consumption, motor cooling energy consumption, battery cooling energy consumption, and equivalent power loss due to battery cooling time. The battery thermal management energy consumption and cooling time cost are unified into an instantaneous cost rate in the power dimension using a normalization algorithm, and the total cost is accumulated through time integration. The weights of cooling time and energy consumption are dynamically adjusted according to real-time operating conditions so that the cost function can adapt to the priority requirements of different scenarios. The cost of cooling time includes the battery's high requirements for operating temperature and the performance loss, lifespan loss, and decreased charge retention capacity caused by the deviation between component temperature and target temperature. The principle and implementation steps for converting it into a unified equivalent power metric are as follows: The cumulative cost expression is: m inst Instantaneous cooling time degradation, r T Cooling rate, r T,max Fastest cooling rate, r T，min Slowest cooling rate; P0 reference power, in kW; q max q min For the extreme value of total energy consumption, t max t min This represents the extreme value of the total time; when r T Approaching r T,max The cooling rate is fast, m inst ≈0, meaning the time penalty is small; n inst P represents the instantaneous energy consumption degradation degree. max P min For minimum and maximum cooling power; when P batcool =P min Lowest energy consumption, n inst =0, meaning the energy penalty is small; P bat，cool (t) The actual power consumed by the battery cooling system at time t, in kW; a: Time degradation weighting coefficient (0≤a≤1), the larger the value, the heavier the penalty for slow cooling; b: Energy consumption degradation weighting coefficient (0≤b≤1), the larger the value, the heavier the penalty for high energy consumption; t0 is the initial time, t f At the terminal time, H(P) ereq ,t) represents the time interval [t0,t1] f The cumulative thermal management energy cost within [the range], where α and β are the diesel engine cooling cost coefficient and the electric motor cooling cost coefficient, respectively; γ is the battery cost coefficient; P mreq (t) The motor's power demand at the current moment; An a / b allocation strategy based on SOC and battery temperature is adopted for dynamic allocation of time and energy consumption. The core objective is to balance load demand, SOC and battery temperature efficiency loss, and battery lifespan. Specifically: Operating Condition 1: SOC is between 50% and 100% and battery temperature T is between 35°C and 0. The time degradation weighting coefficient a = 0 and the energy consumption degradation weighting coefficient b = 0. The battery's additional penalty disappears, and power is used preferentially. Operating Condition 2: SOC is between 50% and 100% and battery temperature T is greater than or equal to 35°C. The time degradation weighting coefficient a = 0.5 - (0.05(T-35)) and the energy consumption degradation weighting coefficient b = 1 - a. That is, for every 1°C increase in battery temperature T, a decreases by 0.

05. Operating Condition 3: SOC is between 50% and 100% and battery temperature T is greater than or equal to 50°C. Time degradation weighting coefficient a = 0, energy consumption degradation weighting coefficient b = 1, and the thermal management system operates at maximum power. Operating Condition 4: SOC ≤ 50%, time degradation weighting coefficient a = 0.5 + (0.05(SOC - 50%) / 100%), energy consumption degradation weighting coefficient b = 1 - a, that is, for every 1% decrease in SOC, a increases by 0.05; Operating Condition 5: SOC < 30%, time degradation weighting coefficient a = 1, energy consumption degradation weighting coefficient b = 0. The system prioritizes energy saving.

7. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: The instantaneous optimization control strategy based on the equivalent cost minimization strategy in step S3 is as follows: Under the constraint of satisfying the boundary conditions, the equivalent fuel consumption is minimized by optimizing the reasonable allocation of the operating state between the diesel engine and the electric motor, thus obtaining the instantaneous optimal diesel engine and battery output power and thermal management power consumption. In high-temperature environments, the cooling system accounts for 10%-20% of the total energy consumption. The main electrical energy-consuming components in the thermal management cooling system reflect the overall energy consumption of the vehicle. Through the control and optimization of the structure and input parameters of the vehicle's powertrain and thermal management cooling systems, the ultimate goal is to reduce energy consumption and improve efficiency. The performance index function based on the strategy of minimizing equivalent energy consumption is... S chg / dis =f(SOC), The Hamiltonian function expression for this optimization problem is as follows: Based on real-time feedback from battery SOC and temperature, the equivalent factor can be adjusted online to obtain a variable equivalent factor related to real-time operating conditions: The weighted moving average method is used to adjust the reference value of the equivalent factor so that the obtained variable equivalent factor has a higher adaptability to the working conditions. The equivalent factor expression is: s ref，k+1 =(1-z)·s ref，k +z·s k Δ=k SOC ·Δ soC +kT·Δ T The operational capabilities of each component are limited by real-world conditions, and the constraints that need to be met include: The cooling equipment in the thermal management system is all powered by batteries. P elec P represents the electric power of the motor. mec Motor mechanical power; Q c (t) Equivalent fuel consumption, j e Oil price, unit: yuan / L; j m Electricity price, unit: yuan / kW·h; η chg η dis These represent the charge and discharge efficiencies of the battery; they are related to the battery properties; where t = k.VT, k = 1, 2, ..., S ref，k S ref，k+1 Here are the equivalent factor reference values ​​calculated for the k-th and (k+1)-th iterations, z is the weight value, and s k+1 Let dSOC be the equivalent factor calculated in the (k+1)th iteration, VT be the sampling period, dSOC be the allowable range of battery SOC variation, dT be the allowable range of battery temperature variation, and l1 and l2 be adjustment parameters. By adjusting these two values, the shape of the penalty function can be controlled, thereby controlling the response speed of the penalty function to changes in battery SOC and battery temperature. Using a tangent function for battery SOC penalty function allows for a rapid response to SOC changes, effectively controlling SOC and battery temperature within a reasonable range. It also enables online adjustment of the equivalent factor, effectively reducing its sensitivity to operating conditions. in，max and P out，max P provides the maximum charge and discharge power for the battery Bat (t) Current charging / discharging power; SOC min The set lower limit for battery SOC; SOC max The upper limit of battery SOC is set, and SOC(t) is the SOC value at the current time; P M,max P is the maximum power of the drive motor. M (t) Current power of the drive motor; P pto,max The maximum power output of the tractor's power output motor, P pto (t) Current power of the power output motor; P ereq,max Maximum power of the diesel engine; x = p1, p2, p3 are the speeds of the cooling water pumps in the three circuits respectively; n e，min and n e,max The minimum and maximum stable speeds of the diesel engine are set; n M,max and n pto,max These are the speed limits for the tractor drive motor and the power output motor, respectively; T e，min and T e，max For diesel engine temperature limiting conditions; T min and T max Allowable temperature variation range for the battery.

8. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: Step S4, based on the output of step S3, rationally allocates energy and, through the integrated architecture of thermal management and energy management bidirectional interaction, couples the thermal management cooling system with the hybrid power system through a logical interface, and transmits the energy consumption required for battery cooling to the corresponding cooling equipment. The real-time power under this operating condition is obtained through the cooling cost factor to achieve bidirectional coupling; the specific method of autoregressive motion control is: P m-b =γ(P bat，cool -P f1 )+k P (T ref -T(t)); Similarly, the cooling circuits of the diesel engine and the electric motor adopt the same control method to achieve cooling energy consumption control; P m-b P is the power of the cooling water pump in the battery cooling circuit. f1 This represents the maximum power of the battery cooling circuit radiator; k P This is the temperature difference coefficient.

9. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: The corresponding output flow rate values ​​are determined for the thermal management cooling circuits of the engine, motor, and battery.

10. The energy optimization method for a thermal management energy consumption coupled hybrid tractor according to claim 1, characterized in that: The cooling circuit also includes an air conditioning heat exchanger model. The compressor maintains the normal operation of the air conditioning system and provides the corresponding flow rate. The flow rate control is based on simulation analysis or a simple flow rate calculation method based on efficiency calculation is directly added to the cooling model.

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