ATS heat dissipation control system of methanol double-engine extended-range excavator

Abstract

The invention discloses an ATS heat dissipation control system of a methanol double-engine extended-range excavator. The ATS heat dissipation control system comprises six independent heat dissipation modules arranged in a partitioned mode, six water pumps, an intelligent pile-up valve and a heat management control unit. The heat dissipation module is arranged in an up-and-down layered mode according to an engine area and a motor electric control area, and electronic fans are evenly distributed in a dot matrix mode and are independently controllable. And the intelligent integrated valve realizes on-demand flow distribution and controlled interconnection among the cooling loops through the main proportional valve and the controllable bypass device. The control method is executed by the thermal management control unit, a virtual thermal pool is constructed and updated by collecting multi-source signals in real time so as to master the thermal state of the system, then global energy efficiency decision making is carried out based on limited time domain rolling optimization, and the priority weight of each control channel is dynamically generated so as to execute active scheduling and accurate control of thermal loads. The cooperative heat dissipation problem of the double-engine extended-range excavator under the multi-heat-source and high-load working conditions is solved, and precise temperature control, energy conservation, consumption reduction and high system reliability are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of excavator heat dissipation, and particularly relates to an ATS heat dissipation control system of a methanol dual-engine range-extended excavator. BACKGROUND

[0002] With the in-depth application of new energy technology in the field of engineering machinery, large excavators adopting a dual-methanol engine range-extended power system have become an important development direction in heavy-load continuous operation scenarios such as mine exploitation and large earthwork engineering, due to their excellent power output, ultra-long endurance and low carbon emission potential. The power system integrates two methanol engines, a range-extender generator set, a high-power drive motor, an electric control system, a high-voltage power battery and other high-power density components, which not only improves the performance of the whole machine, but also generates an unprecedented concentrated high heat load, posing an extreme challenge to the thermal management capability of the whole vehicle.

[0003] At present, the heat dissipation system used in traditional single-engine excavators or ordinary hybrid excavators has the following significant defects when applied to such a complex dual-engine range-extended system, which is difficult to meet the stringent heat dissipation requirements: Firstly, there is a serious contradiction between heat dissipation capacity and vehicle layout. The dual-engine, dual-range-extender and range-extender electric control, dual-drive motor and drive electric control, power battery and other component assemblies are large in size and generate a large amount of heat, with a total heat load far exceeding that of traditional equipment. The capacity and windward area of the traditional single heat dissipation module are limited, and if simply stacked, they will be severely restricted by the vehicle layout space.

[0004] Secondly, there is a problem of large difference in heat source working conditions and extensive heat management. The optimal working temperature range and heat generation characteristics of different components in the system are quite different: the methanol engine needs to maintain a relatively high temperature (about 85℃) to ensure the efficiency of methanol combustion, while the motor, electric control and other power electronic components are sensitive to temperature and require to be stabilized at a relatively low level (about 65℃). The traditional single cooling circuit cannot precisely manage the temperature of each heat source, resulting in low overall system efficiency.

[0005] Thirdly, energy waste is prominent. Traditional heat dissipation fans are usually mechanically driven or simply electrically controlled, and their speed is usually triggered by a single signal, which cannot be accurately matched with the actual total heat load of the dual-engine system. For example, in light load conditions or low temperature environments, the fan may still run at high speed, consuming a large amount of valuable electric energy that could have been used for driving or generating power, directly reducing the energy utilization efficiency and endurance of the whole vehicle.

[0006] Finally, the system lacks necessary thermal safety redundancy. For the key dual-engine power source, if its heat dissipation system shares a core radiator, a blockage, leakage or fan failure of the radiator will cause a significant risk of overheating shutdown of both engines, and the equipment reliability is challenged under severe working conditions.

[0007] Therefore, there is an urgent need for a heat dissipation control system that can solve the problem of coordinated heat dissipation of multiple heat sources, large loads and different working conditions faced by dual-engine range-extended excavators. SUMMARY

[0008] In view of the problems existing in the prior art, the purpose of the present application is to provide an ATS heat dissipation control system for a methanol dual-engine range-extended excavator, so as to realize intelligent thermal management of differentiated precise temperature control and high efficiency and energy saving, and solve the problems of prominent contradiction between heat dissipation capacity and layout, extensive differentiated management of heat sources, serious energy waste and insufficient system redundancy existing in the prior art heat dissipation technology.

[0009] To achieve the above-mentioned purpose, the technical solution adopted by the present application is: An ATS heat dissipation control system for a methanol dual-engine range-extended excavator, comprising six independent heat dissipation modules, six water pumps corresponding to the heat dissipation modules, an intelligent integrated valve, a thermal management control unit and an expansion tank; each heat dissipation module comprises a radiator and at least one electronic fan corresponding to the radiator; the radiator, the corresponding water pump, the intelligent integrated valve and the cooling channel of the power device of the excavator are connected in series to form a heat dissipation loop; The expansion tank is connected to the six heat dissipation loops through a total water supply pipeline and branch interfaces; The thermal management control unit is connected to and controls all electronic fans, water pumps and the intelligent integrated valve; The excavator is provided with an engine heat dissipation area and a motor and electric control heat dissipation area, the engine heat dissipation area is provided with four independent heat dissipation modules connected to the water cooling channels and the intake intercooling channels of the two methanol engines, and the motor and electric control heat dissipation area is provided with two independent heat dissipation modules connected to the cooling channels of the range-extending generator controller and the drive motor controller; The intelligent integrated valve is internally provided with six main channels in one-to-one communication with the heat dissipation module loops, and each main channel is provided with a main proportional valve; a controlled bypass connection device is arranged between each two main channels; the bypass connection device is configured to allow the cooling liquid to flow from one main channel to another main channel under the instruction of the control unit, and the flow direction is controllable; The thermal management control unit is configured to perform the following control process: Step one, system initialization and self-checking, and control all electronic fans to reverse at maximum speed for self-cleaning; Step two, real-time acquisition of heat source state signals, heat dissipation system state signals, whole vehicle working conditions and prediction signals; Step three, based on the acquired signals, dynamically constructing and updating a virtual heat pool model, and real-time outputting a heat state vector containing estimated temperatures of each component, system heat load distribution and residual capacity margin of each heat dissipation partition. Step four, based on the thermal state vector and future predicted load cycle information, a finite time domain rolling optimization decision is made: with the goal of minimizing the total power consumption of all heat dissipation accessories in the future period, under the premise of meeting the temperature safety and performance constraints of each component, the physical constraints and thermodynamic constraints of the actuator, the future optimal control sequence is solved and output, including the fan speed sequence, the valve distribution sequence, and the strategy flag sequence of whether to perform heat load transfer or controllable heat storage / release strategy; Step five, according to the strategy flag in the optimal control sequence, the priority weight of each control channel is dynamically generated; combining the priority weight, the real-time temperature feedback is weighted and processed, the optimal control sequence is fine-tuned, and the final execution instruction is generated to drive the fan and the intelligent integrated valve to act; Step six, online self-learning and environmental adaptation: comparing the difference between the model prediction value and the actual feedback value, the model parameters are fine-tuned online; and the efficient control parameter set under different working conditions is memorized to realize the scene adaptation of the control strategy.

[0010] All electronic fans of the heat dissipation modules are uniformly arranged in a dot matrix manner on the air inlet side, and each electronic fan can be independently controlled by the thermal management control unit. The bypass connection device includes two bypass branches connected in parallel between the two main channels, and each bypass branch is provided with a one-way proportional valve, and the two one-way proportional valves have opposite conduction directions; or the bypass connection device includes a bypass branch connected between the two main channels, and a direction-adjustable bypass one-way valve is arranged on the bypass branch.

[0011] In step two, the collected heat source state signals include: Real-time speed, output torque, and supercharged intake temperature of the two methanol engines; Range-extending motor winding temperature, generator controller board temperature, estimated junction temperature of power devices, DC bus current and voltage of the range-extending motor electronic control system; Drive motor winding temperature, motor controller board temperature, estimated junction temperature of power devices, phase current and voltage of the drive motor electronic control system; Power battery system: highest temperature, lowest temperature and average temperature of the battery pack; The heat dissipation system state signals include: Cooling liquid inlet temperature and outlet temperature of each of the six independent heat dissipation modules; Cooling liquid flow rate of each heat dissipation circuit; Real-time speed feedback of all dot matrix electronic fans; Ambient temperature sensor reading; Current opening degree feedback of each proportional valve of the intelligent integrated valve block; The vehicle working condition and prediction signals include: Real-time drive power request value and range extender generator power request value from the vehicle controller; Predicted load cycle information provided by the vehicle controller; Current operating mode of the vehicle.

[0012] The construction of the virtual hot pool model in step three specifically includes: (1) Dynamic estimation of heat source heat production power For methanol engines, TMCU uses a dynamic estimation model for heat generation power and queries the pre-stored engine efficiency MAP based on real-time speed and torque, combined with coolant temperature rise data, to estimate the waste heat power of the engine water cooling circuit and the intake heat that the intercooler needs to dissipate in real time. For range extender / drive motors, TMCU uses a dynamic heat generation power estimation model and, based on real-time collected motor speed, torque, winding temperature, and current and voltage parameters under current operating conditions, combined with pre-stored 3D MAP diagrams of motor efficiency under different winding temperatures, speeds, and torques, to estimate the instantaneous heat generation power of the motor in real time. For range extender / drive electronic control, TMCU uses a dynamic estimation model of heat generation power and estimates the instantaneous heat generation power of the electronic control module based on the real-time collected output phase current, DC bus voltage, switching frequency and estimated junction temperature of power devices, combined with a pre-stored two-dimensional MAP of heat generation power indexed by output current and coolant temperature. (2) Calculate the heat dissipation efficiency of the radiator and the system heat capacity. TMCU has built-in performance models for each heat dissipation module. These performance models are related to coolant flow rate, inlet temperature difference, fan speed, and ambient temperature. Based on the current flow rate, inlet temperature, and fan speed of each circuit, the instantaneous heat dissipation of each heat dissipation module under the current conditions is predicted in real time. At the same time, the real-time heat capacity of the entire cooling system is calculated; (3) Thermal state vector synthesis and output The estimated heat output power of each heat source is used as the heat inflow term of the virtual heat pool, the predicted heat dissipation of each heat dissipation module is used as the heat outflow term of the virtual heat pool, and the system heat capacity is used as the heat storage capacity term of the virtual heat pool. After integrated calculation, the virtual heat pool outputs a multi-dimensional system current thermal state vector.

[0013] The constraints in step four specifically include: a. Safety constraints: Throughout the entire prediction time domain, the predicted temperature of critical components of each engine, drive motor control unit, and range extender motor control unit must not exceed their absolute safety limit. b. Performance constraints: The temperature of each component should be maintained within its respective high-efficiency operating range as much as possible; c. Actuator constraints: The speed of each fan, the speed of the water pump, and the opening of the valve must be within their respective physical limits, and the rate of change must be smooth; d. Thermodynamic constraints: Energy conservation must be satisfied, that is, the dynamic balance between the changes in heat production, heat dissipation, and heat storage of the system; The heat load transfer strategy is as follows: through the bypass connection device of the intelligent integrated valve, the lower temperature coolant of a certain circuit with surplus heat dissipation capacity is partially guided to another high temperature circuit to participate in heat exchange. When the overall energy consumption is lower, even if the heat dissipation capacity of the high temperature circuit itself is not saturated, the TMCU will actively divert heat through the integrated valve block. Controllable heat storage / release means that certain components with large heat capacity and strong temperature resistance are allowed to temporarily store more heat within a safe temperature range to reduce fan energy consumption; when the system enters a low-load stage, the stored heat is released efficiently by using coolant or increasing air volume.

[0014] In step four, the optimal control sequence is solved and generated as follows: In each control cycle, TMCU re-solves the optimization problem based on the latest system state, and simultaneously evaluates the costs of both operating modes: Mode 1: Each loop operates completely independently; each loop uses only its own resources to control the temperature at the set point, calculate the total power consumption P_independent in this mode; Mode 2: Activate heat load transfer and controllable heat storage / release strategies, and calculate the total power consumption P_strategy under this mode; Decision principle: Compare the total power consumption P_independent in mode 1 with the total power consumption P_strategy in mode 2; If P_strategy is lower than P_independent, then TMCU outputs the optimal sequence containing the corresponding strategy; otherwise, the optimizer outputs the optimal sequence that runs independently.

[0015] The dynamic generation of priority weights in step five specifically involves: When the optimal control sequence indicates the execution of the engine "heat storage" strategy, the control priority weight of the engine's associated heat dissipation channel is reduced. When the optimal control sequence indicates the execution of the "heat load transfer" strategy, the priority weight of the scheduled party's temperature control channel and related bypass valve control channel is increased.

[0016] The online self-learning in step six specifically includes: when there is a systematic deviation between the model's predicted temperature and the actual feedback temperature, the learning algorithm is triggered to fine-tune the parameters in the heat generation model and the heat dissipation model; the scenario adaptation specifically includes: establishing and calling the corresponding set of optimized control parameters for the identified different operating conditions.

[0017] After the above scheme, the application solves the comprehensive heat dissipation problem of the dual-launch extended-range system under multiple heat sources, high load and different working conditions by integrating the hardware architecture of "partition independent heat dissipation, dot matrix fan uniform distribution and valve road intelligent distribution", and introducing the intelligent control algorithm of "virtual heat pool modeling, limited time domain rolling optimization and dynamic priority execution". Under the strict limitation of the whole vehicle layout space, the system successfully realizes the precise temperature management of the key heat sources such as engine, motor and electronic control, so that each component works in its own optimal temperature interval, thereby significantly improving the operating efficiency and component reliability of the whole machine. In terms of energy efficiency, the system dynamically schedules the heat dissipation resources through real-time heat state perception and predictive optimization, and innovatively uses the heat load cross-zone transfer and controllable heat storage / release strategy to effectively avoid the excessive heat dissipation of traditional systems, realize the minimization of the total power consumption of the heat dissipation accessories, and improve the energy economy of the whole machine. At the same time, based on the flexible resource pool concept of global optimization and the hardware design of multi-loop bypass interconnection, the system builds a high-performance heat dissipation capacity redundancy. When a local unit fails or faces extreme heat load, the system can call idle capacity for mutual assistance through intelligent scheduling, ensuring the operation safety and availability of the equipment under continuous heavy load and harsh working conditions, realizing efficient, reliable and intelligent heat management. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is the principle diagram of the application; Figure 2 is the control flowchart of the application. DETAILED DESCRIPTION

[0019] As Figure 1 shown, the application discloses an ATS heat dissipation control system of a methanol dual-launch extended-range excavator, which comprises six independent heat dissipation modules, six water pumps corresponding to the heat dissipation modules, an intelligent integrated valve, a thermal management control unit (TMCU) and an expansion tank. Each heat dissipation module comprises a radiator and at least one electronic fan corresponding to the radiator. In this embodiment, the radiator adopts a GEF core (Gill & Extruded Fin Core). The electronic fan is used to send air to the radiator XINTI. The radiator, the water pump, the intelligent integrated valve and the cooling channel of the power device of the excavator constitute a heat dissipation loop, and the thermal management control unit is connected to and controls the electronic fan, the water pump and the intelligent integrated valve. The expansion tank is connected to the six heat dissipation loops through the total water supply pipeline and branch interfaces, and constitutes the cooling liquid expansion compensation and exhaust hub of the system.

[0020] The six heat dissipation modules are arranged in the space at the right rear part of the excavator, and the space is arranged as two layers of heat dissipation areas, an upper engine heat dissipation area and a lower motor and electric control heat dissipation area. The engine heat dissipation area is provided with four independent heat dissipation modules, namely, a first heat dissipation module, a second heat dissipation module, a third heat dissipation module and a fourth heat dissipation module. The first heat dissipation module is connected with the water cooling channel of the first engine, and the second heat dissipation module is connected with the air intake intercooling channel of the first engine; the third heat dissipation module is connected with the water cooling channel of the second engine, and the fourth heat dissipation module is connected with the air intake intercooling channel of the second engine. The motor and electric control heat dissipation area is provided with two independent heat dissipation modules, namely, a fifth heat dissipation module and a sixth heat dissipation module, the fifth heat dissipation module is connected with the cooling channels of the two sets of range extending generator controllers, and the sixth heat dissipation module is connected with the cooling channels of the two sets of drive motor controllers.

[0021] The electronic fans of the six heat dissipation modules are arranged in a lattice manner at the air inlet side, and the electronic fans of each heat dissipation module are independently controlled, so that different heat dissipation modules can realize differential air supply. In the embodiment, each heat dissipation module is provided with three electronic fans, so that twelve electronic fans are arranged at the air inlet side of the engine heat dissipation area, and six electronic fans are arranged at the air inlet side of the electronic control heat dissipation area. Each electronic fan is responsible for a specific heat dissipation area, forms a uniform negative pressure field, eliminates the difference in wind speed between the center and the edge of the traditional large fan, maximizes the overall heat exchange efficiency, and reduces the dead angle of heat backflow.

[0022] The six water pumps are respectively a first water pump, a second water pump, a third water pump, a fourth water pump, a fifth water pump and a sixth water pump, which are respectively matched with the first heat dissipation module, the second heat dissipation module, the third heat dissipation module, the fourth heat dissipation module, the fifth heat dissipation module and the sixth heat dissipation module.

[0023] The intelligent integrated valve is internally provided with six main channels corresponding to the heat dissipation modules one by one, and each main channel is provided with a main proportional valve. A controlled bypass connection device is arranged between each two main channels, and the bypass connection device is connected at the water outlet side of the main proportional valve. The bypass connection device is configured to allow the cooling liquid to flow from one main channel to another main channel in a controllable direction under the instruction of the control unit.

[0024] In the embodiment, the bypass connection device includes a bypass branch connected between the two main channels, and a direction-adjustable bypass one-way valve is arranged on the bypass branch.

[0025] The bypass connection device includes two bypass branches connected in parallel between the two main channels, and each bypass branch is provided with a one-way proportional valve, and the two one-way proportional valves are opposite in the conduction direction. For example, the two main channels are the first main channel and the second main channel, and the one-way valves on the two bypass branches are the first one-way proportional valve and the second one-way proportional valve. In the state that all the water pumps and the main proportional valves are opened, when the thermal management control unit opens the first one-way proportional valve, part of the coolant in the first main channel will flow to the second main channel through the bypass branch; when the thermal management control unit opens the second one-way proportional valve, part of the coolant in the second main channel will flow to the first main channel through the bypass branch.

[0026] The heat dissipation control method based on the ATS heat dissipation control system is executed by the thermal management control unit (TMCU), and the core is to realize the global energy efficiency optimization and active management of heat flow of the heat dissipation system through the closed loop of "state perception-model prediction-rolling optimization-dynamic execution-online learning". The specific steps are as follows: Step one, system initialization and self-checking. After the whole machine is powered on, the thermal management control unit (TMCU) starts the self-checking program, loads the preset parameters such as heat source heat production model, radiator efficiency model and environmental adaptation parameters. After the self-checking, the TMCU controls all the dot matrix electronic fans to reverse at the maximum speed for a set time (such as 20-30 seconds) to actively clean the surface of the radiator. During this period, the system diagnoses the mechanical state and electrical connection state of the fan by monitoring the working current and feedback speed of each fan. At the same time, it checks whether the communication state and initial reading of each temperature sensor, flow sensor and intelligent integrated valve block are within a reasonable range to complete the system readiness confirmation.

[0027] Step two, real-time acquisition and processing of multi-source signals. TMCU acquires and pre-processes the following multi-source signals in real time through the integrated sensor network and vehicle CAN bus with a fixed control period (such as 100 milliseconds).

[0028] (1) Heat source state signal, including: Two methanol engines: real-time speed, output torque, supercharged intake air temperature; Extended-range motor control system: extended-range motor winding temperature, generator controller board temperature, estimated junction temperature of power devices (such as IGBT), DC bus current and voltage; Drive motor control system: drive motor winding temperature, motor controller board temperature, estimated junction temperature of power devices, phase current and voltage; Power battery system: highest temperature, lowest temperature and average temperature of battery pack.

[0029] (2) Radiator system state signal, including: The inlet temperature and outlet temperature of each of the six independent radiator modules; Each heat dissipation circuit cooling fluid flow rate; Real-time speed feedback of all matrix electronic fans; Ambient temperature sensor reading; Current opening degree feedback of each proportional valve of the intelligent integrated valve block.

[0030] (3) Vehicle working conditions and prediction signals, including: Real-time driving power request value and extended-range power generation power request value from the vehicle controller (VCU); The VCU provides prediction load cycle information for a future period of time (such as 60 to 180 seconds in the future), such as a prediction torque / power demand curve based on typical digging cycles, walking working conditions; Current working mode of the vehicle (such as heavy load digging, light load leveling, walking, idling, etc.).

[0031] After filtering (such as low-pass filtering to remove noise) and reasonable verification (such as range check, change rate limit) of the collected original signals, the standardized engineering values are converted for subsequent modules.

[0032] Step three, virtual heat pool construction and real-time estimation of system thermal state.

[0033] Based on the real-time data processed in step two, the TMCU dynamically constructs and continuously updates a virtual heat pool model reflecting the energy flow and storage state of the entire thermal system inside the controller. This process includes: (1) Dynamic estimation of heat source heat production power For a methanol engine, the TMCU uses a dynamic heat production power estimation model and queries the pre-stored engine efficiency MAP chart (including fuel consumption rate, mechanical efficiency and heat loss distribution under different working conditions) according to real-time speed and torque, combines with cooling liquid temperature rise data to estimate the engine water cooling circuit waste heat power and the air intake heat that needs to be dissipated by the intercooler in real time. The dynamic heat production power estimation model of the methanol engine is as follows:

[0034] Wherein, is the total heat production power of the methanol engine, is the current fuel consumption power (calculated in real time based on fuel injection quantity and fuel heat value); is the engine braking heat efficiency, which is a two-dimensional MAP chart data of speed and torque. is the combustion waste heat distribution coefficient, representing the proportion of combustion loss dissipated through cooling liquid and radiation. represents the mechanical friction heat term, which is a function of speed and can be simplified as a fixed value based on speed lookup table.

[0035] For range-extended / drive motors, TMCU utilizes a dynamic heat generation power estimation model. Based on real-time collected motor speed, torque, winding temperature, and current and voltage parameters under current operating conditions, combined with pre-stored 3D efficiency maps of the motor at different winding temperatures, speeds, and torques, it estimates the instantaneous heat generation power of the motor in real time. The dynamic heat generation power estimation model for range-extended / drive motors is as follows:

[0036] in, For the heat generation power of the range extender / drive motor, This refers to the input / output electrical power of the motor. The efficiency is represented by a three-dimensional MAP graph of winding temperature (T), rotational speed (n), and torque (τ).

[0037] For the range extender / drive electronic control unit (ECU), the TMCU utilizes a dynamic heat generation power estimation model. Based on real-time collected output phase current, DC bus voltage, switching frequency, and estimated junction temperatures of power devices, combined with a pre-stored two-dimensional heat generation power MAP indexed by output current and coolant temperature, the instantaneous heat generation power of the ECU is estimated. The dynamic heat generation power estimation model for the range extender / drive ECU is as follows:

[0038] in, The total heat output of the electronic control module, This is the effective value of the output phase current. The on-state resistance of an IGBT or MOSFET is related to the junction temperature. The function, Duty cycle, Switching loss (W) and switching frequency DC bus voltage Current Related.

[0039] The estimated heat output of each heat source is used as the heat inflow term of the virtual heat pool.

[0040] (2) Calculate the heat dissipation efficiency of the radiator and the system heat capacity. TMCU incorporates performance models for each heat dissipation module, which are linked to parameters such as coolant flow rate, inlet temperature difference, fan speed, and ambient temperature. Based on the current flow rate, inlet temperature, and fan speed of each circuit, it predicts the instantaneous heat dissipation of each heat dissipation module under current conditions.

[0041] The performance models for each heat dissipation module are as follows:

[0042] where, is the instantaneous heat dissipation of the radiator, is the overall heat transfer coefficient of the radiator, which is related to the fin material and structure, and can be considered as a constant or fine-tuned with usage time, is the effective heat dissipation area of the radiator, which is a fixed value, is the logarithmic mean temperature difference between the cooling liquid and the air, calculated from the inlet water temperature , outlet water temperature , and ambient temperature . is the cooling liquid flow rate influence function, typically a relationship that reflects the enhancement of heat transfer coefficient with increased flow rate. is the air flow rate influence function, determined by the speed-flow rate curve of the point array fan.

[0043] At the same time, the real-time heat capacity of the entire cooling system (including all cooling liquids inside the pipeline, radiator core, engine water jacket, motor water channel, and the main metal components in contact with them) is calculated. This takes into account the specific heat capacity, mass of different components, and the temperature and volume of the cooling liquid.

[0044] The predicted heat dissipation of each cooling module is taken as the heat outflow item of the virtual heat pool, and the system heat capacity is taken as the heat storage capacity item of the virtual heat pool.

[0045] (3) Thermal state vector synthesis and output Integrating the above calculations, the virtual heat pool outputs a multi-dimensional system current thermal state vector. This vector not only contains the estimated temperature values of key components (such as engine cylinder, motor winding, and electronic control devices), but also contains the system total heat generation rate, total heat dissipation rate, heat imbalance, current remaining heat dissipation capacity margin of each heat dissipation zone (i.e. how much additional heat can be safely dissipated), and the temperature change trend of key components (such as heating or cooling rate). The discrete-time state space equation of the virtual heat pool is as follows:

[0046] where, is the state variable, i.e. , T i (k) represents the core cooling liquid average temperature of the i-th heat dissipation zone (°C).

[0047] is the natural state coefficient, representing the natural thermal dynamic characteristics of the system without external control and disturbance, i.e. how the temperature of each region naturally evolves over time.

[0048] N is the control variable, i.e. , represents the fan speed of the i-th heat dissipation region.

[0049] is the control input influence coefficient, which linearizes the influence of fan speed on heat dissipation, representing the degree of influence of fan speed control input on the temperature of each region.

[0050] U is the control variable, i.e. , represents the valve opening degree of the i-th heat dissipation region.

[0051] is the control input influence coefficient, which linearizes the influence of valve opening degree on heat dissipation, representing the degree of influence of valve opening degree control input on the temperature of each region.

[0052] is the disturbance vector, i.e. .

[0053] is the disturbance coefficient, representing the degree of influence of heat source heat production on the temperature of each region.

[0054] This heat state vector provides an accurate and comprehensive system heat state map for the subsequent prediction and optimization modules, serving as the basis for global decision-making.

[0055] Step four, energy efficiency decision based on finite time domain rolling optimization TMCU starts a forward-looking rolling optimization calculation process based on the current detailed heat state provided by the virtual heat pool, aiming to optimize the global energy efficiency.

[0056] (1) Future heat load prediction Combining the future load cycle prediction information received from VCU (for example, three consecutive excavations and one rotary unloading will be performed within the next 60 seconds), TMCU inputs the predicted component power demand curve into the heat production power dynamic estimation model in step three, thereby deducing the heat production power change curve of each heat source in the future same period.

[0057] (2) Establish rolling optimization problem TMCU sets a finite time domain (such as the next 60 seconds) as the optimization window. Within this window, the optimization goal is defined as: minimizing the total energy consumed by all heat dissipation accessories, including all dot matrix electronic fans and cooling liquid circulating water pumps, in this period. The optimization objective function is as follows:

[0058] Wherein, J is the target function value, indicating the total energy consumption in the future H time domain; H is the preheating time domain length; i is the unit time step; k is the current time; n is the fan index; Pn(k+i) represents the power consumption of the nth fan at k+i time; Pn(k+i) represents the power consumption of the nth fan at k+i time; is the weight coefficient of the water pump power consumption.

[0059] Multiple constraint conditions are set, mainly including: a. Safety constraint: In the entire prediction time domain, the predicted temperature of the key components of each engine, drive motor electric control and range extender motor electric control should not exceed the absolute safety upper limit (such as engine 110℃, IGBT junction temperature 150℃).

[0060] b. Performance constraint: The temperature of each component should be maintained in the respective high-efficiency working interval (such as engine coolant 85±5℃, motor electric control 65±5℃) to ensure the overall efficiency of the system c. Actuator constraint: The fan speed, water pump speed and valve opening must be within the respective physical limit range (minimum to maximum), and the change rate needs to be smooth to avoid sharp action.

[0061] d. Thermodynamic constraint: Energy conservation must be met, i.e. the dynamic balance of heat generation, heat dissipation and heat storage change of the system.

[0062] Advanced strategy decision: In the optimization problem, the following two strategies are allowed as decision variables to further reduce the total power consumption under the premise of meeting the constraints: Strategy A (thermal load carrying): Through the controlled bypass of the intelligent integrated valve, the lower temperature coolant of a certain heat dissipation capacity surplus loop (resource side) is partially guided to another high temperature loop (demand side) to participate in heat exchange, and when the overall energy consumption is lower, the TMCU will actively guide the heat through the integrated valve block even if the heat dissipation capacity of the high temperature loop itself is not saturated. For example, when the ambient temperature is low, even if the drive motor electric control heat dissipation water pump or heat dissipation fan is not at full load, a part of the heat of the heat dissipation water circuit will be dispatched to the upper intercooled heat dissipation water circuit (at this time the intercooling demand is low and the fan efficiency is high) for auxiliary heat dissipation.

[0063] Strategy B (Controllable heat storage / release): Allow some components with large heat capacity and strong temperature variation tolerance (such as the engine) to temporarily store more heat within a safe temperature range (allow it to work for a short time with overheat), so as to reduce fan power consumption. When the system enters a low load stage, use cooling liquid or increase air volume for efficient "heat release" to dissipate the stored heat. That is, it is equivalent to using the component itself as a short-term "heat pool" to smooth out the peak of the heat dissipation power, so that the heat dissipation system always works in the high energy efficiency area.

[0064] (3) Solve and generate the optimal control sequence: TMCU solves the above optimization problem based on the latest system state at each control cycle (such as every 10 seconds). Using the built-in optimization algorithm (such as the model predictive control algorithm), a series of optimal control actions within the future optimization window are calculated.

[0065] TMCU will re-solve this problem at each control cycle. It will evaluate the cost of two operating modes at the same time: Mode 1: Each loop runs completely independently. Each loop only uses its own resources to control the temperature at the set point, and the total power consumption P_independent in this mode is calculated.

[0066] Mode 2: Enable strategy A and / or B, and calculate the total power consumption P_strategy in this mode. For example, transfer some heat from loop A to loop B (strategy A), or allow loop C to temporarily rise in temperature by 3°C (strategy B).

[0067] Decision principle: Compare the total power consumption P_independent of mode 1 and the total power consumption P_strategy of mode 2.

[0068] If P_strategy is significantly lower than P_independent (for example, more than 5% lower), then TMCU outputs the optimal sequence containing the corresponding strategy.

[0069] If they are similar, or P_strategy is even higher (for example, the valve power consumption brought by scheduling itself offsets the fan power saving), then the optimizer outputs the optimal sequence of independent operation.

[0070] This action sequence specifies the set point for each shorter control interval (such as 1 second) in the future in detail, mainly including: Fan speed sequence: The future target speed of the point array fan of each heat dissipation module in the engine heat dissipation area and the point array fan of each module in the lower motor control area.

[0071] Valve distribution sequence: In the intelligent integrated valve block, the target opening sequence of each main proportional valve, and the target opening and conduction direction sequence of each bypass connection device (bypass one-way proportional valve). This determines the distribution ratio of coolant between each circuit and the cross-zone flow rate.

[0072] Strategy flag sequence: Clearly marks which times the heat load transfer or heat storage / release strategy was executed, as well as the corresponding scheduling relationship or heat storage component.

[0073] Step 5: Dynamic allocation and execution control.

[0074] Based on the optimization results, TMCU dynamically generates priority weights for each control channel (temperature signal). For example, when the algorithm decides to allow the engine to "store heat," the control priority weights of its heat dissipation channels, such as pumps, fans, and valves, will be temporarily lowered; when it decides to perform "heat load transfer" for electronic control, the priority of the relevant valve control channels will increase sharply.

[0075] The lower execution layer receives the setpoint sequence (fan speed, water pump speed, and centralized valve opening) output by the optimization layer, and performs fine-tuning based on the real-time temperature feedback after dynamic weighting, generating the final PWM and valve control commands to drive hardware execution.

[0076] The synthesized final instruction is then converted into specific actuator drive signals: a. Fan drive: Generates pulse width modulation (PWM) signals to drive the motor controllers of each dot matrix electronic fan, precisely controlling their speed.

[0077] b. Valve block drive: Generates analog voltage or current signals to control the opening degree of each electronically controlled proportional valve (including the main proportional valve and the bypass check valve) in the intelligent integrated valve block, and precisely adjusts the coolant flow rate and direction.

[0078] Step Six: Online Self-Learning and Environment Adaptation To achieve continuous optimization and personalization of control strategies, the system possesses online learning capabilities: Online self-calibration of model parameters: TMCU continuously compares the temperature change trajectory predicted by the virtual thermal pool model with the actual sensor feedback temperatures of each component. When a systematic deviation exists between the prediction and the actual measurement, the learning algorithm is triggered to fine-tune the key parameters in the heat generation and heat dissipation models, making the virtual thermal pool model more accurately reflect the actual physical system.

[0079] Contextualized memory and adaptation of control strategies: The system automatically records a set of control parameters (including priority, temperature setpoint, etc.) that have been verified to achieve efficient and stable operation under different typical operating conditions.

[0080] With the accumulation of operation data, the TMCU can establish and optimize the dedicated control strategy graph for different scenes. When the current operation scene is identified as similar to the historical scene, the corresponding optimized parameters can be quickly called or fused to realize the individualization and scene-based quick adaptation of the control strategy.

[0081] Compared with the prior art, the present application has the following beneficial effects: High efficiency and compactness, solving the layout problem: through the hardware architecture of "partition independent cooling, dot matrix fan uniform distribution, valve road intelligent distribution", the precise "point-to-point" cooling of each heat source is realized in the limited cabin space of the double-launching extended excavator, ensuring that the drive motor electric control, extended motor electric control and engine work in their respective optimal temperature range, improving the reliability and efficiency of the whole machine Significant energy-saving effect: the integrated valve block series-parallel waterway design realizes intelligent heat energy allocation between cold and hot sources, and the local precise control of electronic dot matrix fans avoids unnecessary energy consumption.

[0082] Maximum resource utilization: through global optimization, the heat dissipation capacity of the whole system is scheduled as a flexible resource pool, breaking through the hardware limit of physical partitioning, realizing the "peak load shifting" of heat dissipation capacity, minimizing the total power consumption of fans, water pumps and other heat dissipation accessories under the premise of meeting the temperature safety constraints of each component, improving the vehicle's endurance or fuel economy.

[0083] High reliability and redundancy: the multi-zone physical isolation design combined with the software heat scheduling strategy restructures the idle heat dissipation capacity built-in the system, realizes the high cost-effective system-level redundancy, and provides protection for the reliable operation of the whole machine. Local failure of a single heat dissipation module no longer leads to whole machine failure downtime.

[0084] The above is only an embodiment of the present application, and does not limit the technical scope of the present application in any way. Therefore, any minor modification, equivalent change and modification made according to the technical essence of the present application to the above embodiment still falls within the scope of the present application.

Claims

1. An ATS (Automatic Temperature Regulator) control system for a methanol dual-engine range extender excavator, characterized in that, It includes six independent heat dissipation modules, six water pumps corresponding to each heat dissipation module, a smart integrated valve, a thermal management control unit, and an expansion tank; Each of the heat dissipation modules includes a radiator and at least one electric fan corresponding to the radiator; the radiator, the corresponding water pump, the intelligent integrated valve, and the excavator's power device cooling channel are connected in series to form a heat dissipation circuit; The expansion tank is connected to six heat dissipation circuits via a main water supply pipeline and branch interfaces. The thermal management control unit connects to and controls all electric fans, water pumps, and the intelligent integrated valve; The excavator is equipped with an engine cooling area and a motor and electronic control cooling area. The engine cooling area has four independent cooling modules, which are respectively connected to the water cooling channel and the intake intercooling channel of the two methanol engines. The motor and electronic control cooling area has two independent cooling modules, which are respectively connected to the cooling channel of the range extender generator controller and the drive motor controller. The intelligent integrated valve has six main channels that are connected to the heat dissipation module circuit one by one, and each main channel is equipped with a main proportional valve; a controlled bypass connection device is provided between every two main channels; the bypass connection device is configured to allow coolant to flow directionally from one main channel to another under the command of the control unit, and the flow direction is controllable. The thermal management control unit is configured to perform the following control process: Step 1: System initialization and self-test, and control all electric fans to reverse at maximum speed for self-cleaning; Step 2: Real-time acquisition of heat source status signals, cooling system status signals, vehicle operating conditions and prediction signals; Step 3: Based on the collected signals, dynamically construct and update the virtual heat pool model, and output the thermal state vector in real time, which includes the estimated temperature of each component, the system heat load distribution, and the remaining capacity margin of each heat dissipation zone. Step 4: Based on the thermal state vector and the future predicted load cycle information, perform finite time domain rolling optimization decision: With the goal of minimizing the total power consumption of all heat dissipation accessories in the future period, under the premise of satisfying the temperature safety and performance constraints of each component, the physical constraints of the actuator and the thermodynamic constraints, solve and output the future optimal control sequence. The optimal control sequence includes the fan speed sequence, the valve allocation sequence and the strategy flag sequence of whether to execute the heat load transfer or the controllable heat storage / release strategy. Step 5: Based on the strategy flags in the optimal control sequence, dynamically generate the priority weights of each control channel; combine the priority weights to perform weighted processing on the real-time temperature feedback, fine-tune the optimal control sequence, and generate the final execution command to drive the fan and intelligent integrated valve to operate. Step Six: Online Self-Learning and Environment Adaptation: Compare the differences between the model's predicted values ​​and the actual feedback values, fine-tune the model parameters online, and memorize the set of efficient control parameters under different operating conditions to achieve scenario-based adaptation of the control strategy.

2. The ATS heat dissipation control system for a methanol dual-engine range extender excavator according to claim 1, characterized in that, All the electronic fans of the heat dissipation modules are evenly arranged in a dot matrix on their air intake side, and each electronic fan can be independently controlled by the thermal management control unit. The bypass connection device includes two bypass branches connected in parallel between the two main channels, each bypass branch is provided with a one-way proportional valve, and the two one-way proportional valves have opposite conduction directions; or, the bypass connection device includes a bypass branch connected between the two main channels, the bypass branch is provided with a one-way bypass valve with adjustable direction.

3. The ATS heat dissipation control system for a methanol dual-engine range extender excavator according to claim 1, characterized in that, In step two, the collected heat source status signals include: Real-time speed, output torque, and intake air temperature after boosting of the two methanol engines; The range extender motor control system includes the range extender motor winding temperature, generator controller board temperature, estimated junction temperature of power devices, and DC bus current and voltage. The drive motor control system includes the drive motor winding temperature, motor controller board temperature, estimated junction temperature of power devices, phase current and voltage; Power battery system: maximum temperature, minimum temperature and average temperature of the battery pack; The status signals of the heat dissipation system include: The coolant inlet and outlet temperatures of each of the six independent heat dissipation modules; Coolant flow rate in each heat dissipation circuit; Real-time speed feedback for all dot matrix electronic fans; Ambient temperature sensor reading; Feedback on the current opening degree of each proportional valve in the intelligent integrated valve block; The vehicle operating condition and prediction signals include: Real-time drive power request value and range extender generator power request value from the vehicle controller; Predicted load cycle information provided by the vehicle controller; Current operating mode of the vehicle.

4. The ATS heat dissipation control system for a methanol dual-engine range extender excavator according to claim 1, characterized in that, The construction of the virtual hot pool model in step three specifically includes: (1) Dynamic estimation of heat source heat production power For methanol engines, TMCU uses a dynamic estimation model for heat generation power and queries a pre-stored engine efficiency MAP based on real-time speed and torque, combined with coolant temperature rise data, to estimate the waste heat power of the engine water cooling circuit and the intake heat that the intercooler needs to dissipate in real time. For range extender / drive motors, TMCU uses a dynamic heat generation power estimation model and, based on real-time collected motor speed, torque, winding temperature, and current and voltage parameters under current operating conditions, combined with pre-stored 3D MAP diagrams of motor efficiency under different winding temperatures, speeds, and torques, to estimate the instantaneous heat generation power of the motor in real time. For range extender / drive electronic control, TMCU uses a dynamic estimation model for heat generation power and estimates the instantaneous heat generation power of the electronic control module based on real-time collected output phase current, DC bus voltage, switching frequency and estimated junction temperature of power devices, combined with a pre-stored two-dimensional MAP of heat generation power indexed by output current and coolant temperature. (2) Calculate the dynamic prediction of radiator heat dissipation efficiency and system heat capacity TMCU has built-in performance models for each heat dissipation module. These performance models are related to coolant flow rate, inlet temperature difference, fan speed, and ambient temperature. Based on the current flow rate, inlet temperature, and fan speed of each circuit, the instantaneous heat dissipation of each heat dissipation module under the current conditions is predicted in real time. At the same time, the real-time heat capacity of the entire cooling system is calculated; (3) Thermal state vector synthesis and output The estimated heat output power of each heat source is used as the heat inflow term of the virtual heat pool, the predicted heat dissipation of each heat dissipation module is used as the heat outflow term of the virtual heat pool, and the system heat capacity is used as the heat storage capacity term of the virtual heat pool. After integrated calculation, the virtual heat pool outputs a multi-dimensional system current thermal state vector.

5. The ATS heat dissipation control system for a methanol dual-engine range extender excavator according to claim 1, characterized in that, The constraints in step four specifically include: a. Safety constraints: Throughout the entire prediction time domain, the predicted temperature of critical components of each engine, drive motor control unit, and range extender motor control unit must not exceed their absolute safety limit. b. Performance constraints: The temperature of each component should be maintained within its respective high-efficiency operating range as much as possible; c. Actuator constraints: The speed of each fan, the speed of the water pump, and the opening of the valve must be within their respective physical limits, and the rate of change must be smooth; d. Thermodynamic constraints: Energy conservation must be satisfied, that is, the dynamic balance between the changes in heat production, heat dissipation, and heat storage of the system; The heat load transfer strategy is as follows: through the bypass connection device of the intelligent integrated valve, the lower temperature coolant of a certain circuit with surplus heat dissipation capacity is partially guided to another high temperature circuit to participate in heat exchange. When the overall energy consumption is lower, even if the heat dissipation capacity of the high temperature circuit itself is not saturated, the TMCU will actively divert heat through the integrated valve block. Controllable heat storage / release means that certain components with large heat capacity and strong temperature resistance are allowed to temporarily store more heat within a safe temperature range to reduce fan energy consumption; when the system enters a low-load stage, the stored heat is released efficiently by using coolant or increasing air volume.

6. The ATS heat dissipation control system for a methanol dual-engine range extender excavator according to claim 1, characterized in that, In step four, the optimal control sequence is solved and generated as follows: In each control cycle, TMCU re-solves the optimization problem based on the latest system state, and simultaneously evaluates the costs of both operating modes: Mode 1: Each loop operates completely independently; each loop uses only its own resources to control the temperature at the set point, calculate the total power consumption P_independent in this mode; Mode 2: Activate heat load transfer and controllable heat storage / release strategies, and calculate the total power consumption P_strategy under this mode; Decision principle: Compare the total power consumption P_independent in mode 1 with the total power consumption P_strategy in mode 2; If P_strategy is lower than P_independent, then TMCU outputs the optimal sequence containing the corresponding strategy; otherwise, the optimizer outputs the optimal sequence that runs independently.

7. The ATS heat dissipation control system for a methanol dual-engine range extender excavator according to claim 1, characterized in that, The dynamic generation of priority weights in step five specifically involves: When the optimal control sequence indicates the execution of the engine "heat storage" strategy, the control priority weight of the engine's associated heat dissipation channel is reduced. When the optimal control sequence indicates the execution of the "heat load transfer" strategy, the priority weight of the scheduled party's temperature control channel and related bypass valve control channel is increased.

8. The ATS heat dissipation control system for a methanol dual-engine range extender excavator according to claim 1, characterized in that, The online self-learning in step six specifically includes: when there is a systematic deviation between the model's predicted temperature and the actual feedback temperature, the learning algorithm is triggered to fine-tune the parameters in the heat generation model and the heat dissipation model; the scenario adaptation specifically includes: establishing and calling the corresponding set of optimized control parameters for the identified different operating conditions.

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