Methanol dual-launch range-extended excavator ATS heat dissipation control system

Abstract

The application discloses a kind of ATS heat dissipation control systems of methanol double-launch range-prolonging excavator, it includes six independent heat dissipation modules arranged in six water pumps, an intelligent integrated valve and heat management control unit.The heat dissipation module is arranged in layers according to engine area and motor electric control area, and the electronic fan is evenly distributed in dot matrix mode and independently controllable.Intelligent integrated valve realizes the flow distribution and controlled interconnection between each cooling circuit according to demand by main proportional valve and controllable bypass device.Control method is executed by heat management control unit, and the system thermal state is mastered by constructing and updating virtual heat pool by real-time acquisition of multiple source signals, and then global energy efficiency decision is made based on finite time domain rolling optimization, and priority weight of each control channel is dynamically generated to execute thermal load active scheduling and accurate control.The application solves the problem of collaborative heat dissipation of double-launch range-prolonging excavator under high-load working condition of multiple heat sources, realizes accurate temperature control, energy saving and consumption reduction and system high reliability.

Description

Technical Field

[0001] This invention relates to the field of excavator heat dissipation technology, specifically to an ATS heat dissipation control system for a methanol dual-engine range extender excavator. Background Technology

[0002] With the deepening application of new energy technologies in the construction machinery field, large excavators using dual methanol engine range-extended power systems have become an important development direction for heavy-duty continuous operation scenarios such as mining and large-scale earthmoving projects, due to their excellent power output, ultra-long range, and low carbon emission potential. This power system integrates multiple high-power-density components such as two methanol engines, range-extended generator sets, high-power drive motors and electronic control systems, and high-voltage power batteries. While improving the overall machine performance, it also generates unprecedented concentrated high heat loads, posing extreme challenges to the vehicle's thermal management capabilities.

[0003] Currently, the cooling systems used in traditional single-engine excavators or ordinary hybrid excavators exhibit the following significant shortcomings when applied to such complex dual-engine range-extender systems, making it difficult to meet their stringent cooling requirements:

[0004] First, there is a significant conflict between heat dissipation capacity and overall vehicle layout. The assemblies of dual engines, dual range extenders and range extender electronic controls, dual drive motors and drive electronic controls, and power batteries are large in size and generate a large amount of heat, with the total heat load far exceeding that of traditional equipment. The capacity and frontal area of ​​traditional single heat dissipation modules are limited, and simple stacking would be severely constrained by the overall vehicle layout space.

[0005] Secondly, there are issues with significant differences in heat source operating conditions and inadequate thermal management. The optimal operating temperature ranges and heat dissipation characteristics of different components in the system vary considerably: the methanol engine requires maintaining a relatively high temperature (approximately 85°C) to ensure methanol combustion efficiency, while power electronic components such as the motor and electronic control system are more temperature-sensitive and require stable operation at a lower level (approximately 65°C). Traditional single-cooling circuits cannot provide precise temperature management for each heat source, resulting in overall system inefficiency.

[0006] Secondly, energy waste is a significant issue. Traditional cooling fans often employ mechanical drives or simple electronic controls, and their speed is typically triggered by a single signal, making it impossible to precisely match the actual total heat load of the dual-engine system. For example, under light load conditions or in low-temperature environments, the fan may still continue to operate at high speed, consuming a large amount of valuable electrical energy that could be used for driving or generating electricity, directly reducing the vehicle's energy efficiency and range.

[0007] Finally, the system lacks necessary thermal safety redundancy. For critical dual-engine power sources, if their cooling systems share a core radiator, blockage, leakage, or fan failure in that radiator will lead to a significant risk of both engines overheating and shutting down simultaneously, posing a challenge to equipment reliability under harsh operating conditions.

[0008] Therefore, there is an urgent need for a heat dissipation control system that can solve the problem of coordinated heat dissipation under multiple heat sources, heavy loads, and different working conditions faced by twin-engine extended-range excavators. Summary of the Invention

[0009] In view of the problems existing in the prior art, the purpose of this invention is to provide an ATS heat dissipation control system for a methanol dual-engine range extender excavator, so as to achieve differentiated and precise temperature control and efficient energy-saving intelligent thermal management, and solve the problems of prominent contradiction between heat dissipation capacity and layout, extensive management of heat source differentiation, serious energy waste and insufficient system redundancy in the existing heat dissipation technology.

[0010] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0011] An ATS heat dissipation control system for a methanol dual-engine range extender excavator includes six independent heat dissipation modules, six water pumps corresponding to each heat dissipation module, an intelligent integrated valve, a thermal management control unit, and an expansion tank; each heat dissipation module 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 cooling channel of the excavator's power components are connected in series to form a heat dissipation circuit;

[0012] The expansion tank is connected to six heat dissipation circuits via a main water supply pipeline and branch interfaces.

[0013] The thermal management control unit connects to and controls all electric fans, water pumps, and the intelligent integrated valve;

[0014] 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.

[0015] 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.

[0016] The thermal management control unit is configured to perform the following control process:

[0017] Step 1: System initialization and self-test, and control all electric fans to reverse at maximum speed for self-cleaning;

[0018] Step 2: Real-time acquisition of heat source status signals, cooling system status signals, vehicle operating conditions and prediction signals;

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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.

[0025] In step two, the collected heat source status signals include:

[0026] Real-time speed, output torque, and intake air temperature after boosting of the two methanol engines;

[0027] 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.

[0028] 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;

[0029] Power battery system: maximum temperature, minimum temperature and average temperature of the battery pack;

[0030] The status signals of the heat dissipation system include:

[0031] The coolant inlet and outlet temperatures of each of the six independent heat dissipation modules;

[0032] Coolant flow rate in each heat dissipation circuit;

[0033] Real-time speed feedback for all dot matrix electronic fans;

[0034] Ambient temperature sensor reading;

[0035] Feedback on the current opening degree of each proportional valve in the intelligent integrated valve block;

[0036] The vehicle operating condition and prediction signals include:

[0037] Real-time drive power request value and range extender generator power request value from the vehicle controller;

[0038] Predicted load cycle information provided by the vehicle controller;

[0039] Current operating mode of the vehicle.

[0040] The construction of the virtual hot pool model in step three specifically includes:

[0041] (1) Dynamic estimation of heat source heat production power

[0042] 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.

[0043] 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.

[0044] 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.

[0045] (2) Calculate the heat dissipation efficiency of the radiator and the system heat capacity.

[0046] 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.

[0047] At the same time, the real-time heat capacity of the entire cooling system is calculated;

[0048] (3) Thermal state vector synthesis and output

[0049] 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.

[0050] The constraints in step four specifically include:

[0051] 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.

[0052] b. Performance constraints: The temperature of each component should be maintained within its respective high-efficiency operating range as much as possible;

[0053] 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;

[0054] 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;

[0055] 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.

[0056] 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.

[0057] In step four, the optimal control sequence is solved and generated as follows:

[0058] 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:

[0059] 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;

[0060] Mode 2: Activate heat load transfer and controllable heat storage / release strategies, and calculate the total power consumption P_strategy under this mode;

[0061] Decision principle: Compare the total power consumption P_independent in mode 1 with the total power consumption P_strategy in mode 2;

[0062] 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.

[0063] The dynamic generation of priority weights in step five specifically involves:

[0064] 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.

[0065] 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.

[0066] 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.

[0067] By adopting the above-mentioned solution, this invention systematically solves the comprehensive heat dissipation problem faced by dual-engine range extender systems under multiple heat sources, high loads, and different operating conditions by integrating a hardware architecture of "zoned independent heat dissipation, matrix fan distribution, and intelligent valve allocation" and introducing intelligent control algorithms of "virtual heat pool modeling, finite time domain rolling optimization, and dynamic priority execution." Under the strict constraints of vehicle layout space, this system successfully achieves precise temperature management of key heat sources such as the engine, motor, and electronic control system, ensuring that each component operates within its optimal temperature range, thereby significantly improving overall operating efficiency and component reliability. In terms of energy efficiency, the system dynamically schedules heat dissipation resources through real-time thermal state perception and predictive optimization, and innovatively employs cross-zone heat load transfer and controllable heat storage / release strategies, effectively avoiding excessive heat dissipation in traditional systems, minimizing the total power consumption of heat dissipation accessories, and improving the overall energy economy of the system. Meanwhile, based on the concept of a globally optimized flexible resource pool and a hardware design with multi-loop bypass interconnection, the system has built a high-performance and cost-effective heat dissipation redundancy. When a local unit fails or faces extreme heat load, it can use the system's idle capacity for mutual assistance through intelligent scheduling, ensuring the safe operation and availability of the equipment under continuous heavy load and harsh working conditions, and achieving efficient, reliable and intelligent thermal management. Attached Figure Description

[0068] Figure 1 This is a schematic diagram of the principle of the present invention;

[0069] Figure 2 This is the control flowchart of the present invention. Detailed Implementation

[0070] like Figure 1 As shown, this invention discloses an ATS (Active Thermal System) cooling control system for a methanol dual-engine range extender excavator, comprising six independent cooling modules, six water pumps corresponding to each cooling module, an intelligent integrated valve, a thermal management control unit (TMCU), and an expansion tank. Each cooling module includes a radiator and at least one electric fan corresponding to that radiator. In this embodiment, the radiator uses a finned + extruded fin core (GEF core). The electric fan supplies air to the radiator. The radiator, water pumps, intelligent integrated valve, and cooling channels for the excavator's power components constitute a cooling circuit. The thermal management control unit connects to and controls the electric fan, water pumps, and intelligent integrated valve. The expansion tank is connected to the six cooling circuits via a main water supply line and branch interfaces, forming the system's coolant expansion compensation and exhaust hub.

[0071] Six cooling modules are located in the space at the right rear of the excavator. This space is arranged into two layers: the upper layer is for engine cooling, and the lower layer is for motor and electronic control systems. The engine cooling area has four independent cooling modules: the first, second, third, and fourth. The first module connects to the water-cooling channel of engine number one, and the second module connects to the intake intercooling channel of engine number one; the third module connects to both the water-cooling and intake intercooling channels of engine number two. The motor and electronic control system cooling area has two independent cooling modules: the fifth and sixth. The fifth module connects to the cooling channels of the two range extender generator controllers, and the sixth module connects to the cooling channels of the two drive motor controllers.

[0072] The electronic fans of the six heat dissipation modules are arranged in a dot matrix on the air intake side, and each heat dissipation module's electronic fan is independently controlled, allowing for differentiated airflow between different heat dissipation modules. In this embodiment, one radiator is equipped with three electronic fans, so twelve electronic fans are arranged on the air intake side of the engine cooling area, and six electronic fans are arranged on the air intake side of the electronically controlled cooling area. Each electronic fan is responsible for a specific heat dissipation area, forming a uniform negative pressure field, eliminating the wind speed difference between the center and edge of a traditional large fan, maximizing overall heat exchange efficiency, and reducing dead zones for heat recirculation.

[0073] The six water pumps are designated as the first water pump, the second water pump, the third water pump, the fourth water pump, the fifth water pump, and the sixth water pump, which are respectively connected to 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.

[0074] The intelligent integrated valve has six main channels, each corresponding to a heat dissipation module, and each main channel is equipped with a main proportional valve. A controlled bypass connection is provided between every two main channels, connected to the outlet side of the main proportional valve. This bypass connection is configured to allow coolant to flow directionally from one main channel to another under controllable instructions from the control unit.

[0075] In this embodiment, the bypass connection device includes a bypass branch connecting the two main channels, and a bypass one-way valve with adjustable direction is provided on the bypass branch.

[0076] The bypass connection device includes two bypass branches connected in parallel between the two main channels. Each bypass branch is equipped with a one-way proportional valve, and the two one-way proportional valves have opposite conduction directions. For example, the two main channels are a first main channel and a second main channel, and the one-way valves on the two bypass branches are a first one-way proportional valve and a second one-way proportional valve, respectively. With all water pumps and main proportional valves open, when the thermal management control unit opens the first one-way proportional valve, a portion of the coolant in the first main channel flows to the second main channel through the bypass branch; when the thermal management control unit opens the second one-way proportional valve, a portion of the coolant in the second main channel flows to the first main channel through the bypass branch.

[0077] The heat dissipation control method based on the above-mentioned ATS heat dissipation control system is executed by the thermal management control unit (TMCU). Its core lies in achieving optimal global energy efficiency and proactive heat flow management of the heat dissipation system through a closed loop of "state awareness - model prediction - rolling optimization - dynamic execution - online learning." The specific steps are as follows:

[0078] Step 1: System Initialization and Self-Test. After the entire unit is powered on, the Thermal Management Control Unit (TMCU) initiates a self-test program, loading preset parameters such as heat generation models for each heat source, radiator performance models, and environmental adaptation parameters. After the self-test passes, the TMCU controls all dot-matrix electronic fans to reverse at maximum speed for a set duration (e.g., 20-30 seconds) to actively clean the radiator surface. During this period, the system monitors the operating current and feedback speed of each fan to perform a preliminary diagnosis of the fan's mechanical and electrical connection status. Simultaneously, it checks the communication status and initial readings of each temperature sensor, flow sensor, and intelligent integrated valve block to ensure they are within reasonable ranges, thus confirming system readiness.

[0079] Step 2: Real-time acquisition and processing of multi-source signals. The TMCU integrates a sensor network with the vehicle's CAN bus to acquire and preprocess the following multi-source signals in real time at a fixed control cycle (e.g., 100 milliseconds).

[0080] (1) Heat source status signal, including:

[0081] Two methanol engines: real-time speed, output torque, and intake air temperature after boosting;

[0082] Range extender motor electronic control system: range extender motor winding temperature, generator controller board temperature, estimated junction temperature of power devices (such as IGBTs), DC bus current and voltage;

[0083] Drive motor electronic control system: drive motor winding temperature, motor controller board temperature, estimated junction temperature of power devices, phase current and voltage;

[0084] Power battery system: maximum temperature, minimum temperature and average temperature of battery pack.

[0085] (2) Status signals of the heat dissipation system, including:

[0086] The coolant inlet and outlet temperatures of each of the six independent heat dissipation modules;

[0087] Coolant flow rate in each heat dissipation circuit;

[0088] Real-time speed feedback for all dot matrix electronic fans;

[0089] Ambient temperature sensor reading;

[0090] Feedback on the current opening degree of each proportional valve in the intelligent integrated valve block.

[0091] (3) Vehicle operating conditions and prediction signals, including:

[0092] Real-time drive power request value and range extender generator power request value from the vehicle control unit (VCU);

[0093] The VCU provides predicted load cycle information for a future period of time (such as the next 60 to 180 seconds), such as predicted torque / power demand curves based on typical digging cycles and walking conditions.

[0094] The current working mode of the vehicle (such as heavy-duty excavation, light-duty leveling, traveling, idling, etc.).

[0095] The acquired raw signals are filtered (e.g., low-pass filtering to remove noise) and validated for reasonableness (e.g., range checking, rate of change limiting) before being converted into standardized engineering values ​​for use by subsequent modules.

[0096] Step 3: Construction of virtual heat pool and real-time estimation of system thermal state.

[0097] Based on the real-time data processed in step two, TMCU dynamically constructs and continuously updates a virtual thermal pool model reflecting the energy flow and storage status of the entire thermal system within the controller. This process includes:

[0098] (1) Dynamic estimation of heat source heat production power

[0099] For methanol engines, TMCU utilizes a dynamic heat production power estimation model and, based on real-time engine speed and torque, queries a pre-stored engine efficiency MAP (containing fuel consumption rate, mechanical efficiency, and heat loss distribution under different operating conditions). Combined with coolant temperature rise data, it estimates in real-time the waste heat power of the engine's water-cooling circuit and the intake heat that the intercooler needs to dissipate. The dynamic heat production power estimation model for methanol engines is as follows:

[0100]

[0101] in, This represents the total heat output of the methanol engine. The current fuel consumption power (calculated in real time based on fuel injection quantity and fuel calorific value); The data represents the engine braking thermal efficiency, and the data represents the two-dimensional MAP data of speed and torque. The combustion waste heat distribution coefficient represents the proportion of combustion losses lost through coolant and radiation. The term representing heat generation from mechanical friction is a function of rotational speed and can be simplified to a fixed value obtained by looking up a table based on rotational speed.

[0102] 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:

[0103]

[0104] 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 of the motor is represented by a three-dimensional MAP graph of winding temperature (T), speed (n), and torque (τ).

[0105] 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:

[0106]

[0107] in, The total heat generation power 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,

[0108] Switching loss (W) and switching frequency DC bus voltage Current Related.

[0109] The estimated heat output of each heat source is used as the heat inflow term of the virtual heat pool.

[0110] (2) Calculate the heat dissipation efficiency of the radiator and the system heat capacity.

[0111] 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.

[0112] The performance models for each heat dissipation module are as follows:

[0113]

[0114] in, This refers to the instantaneous heat dissipation of the radiator. The overall heat transfer coefficient of the radiator is related to the fin material and structure, and can be considered a constant or slightly adjusted over time. The effective heat dissipation area of ​​the radiator is a fixed value. The logarithmic mean temperature difference between the coolant and air is given by the inlet water temperature. outlet water temperature Ambient temperature The calculation yielded the result. This is a function of the influence of coolant flow rate, typically expressed as: The relationship reflects the enhancement of the heat transfer coefficient due to the increase in flow rate. The airflow velocity influence function is determined by the speed-airflow curve of the lattice fan.

[0115] Simultaneously, the real-time heat capacity of the entire cooling system (including all coolant inside the pipes, radiator core, engine water jacket, motor water passages, etc., as well as the main metal components in contact with them) is calculated. This takes into account the specific heat capacity and mass of the materials of different components, as well as the temperature and volume of the coolant.

[0116] 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.

[0117] (3) Thermal state vector synthesis and output

[0118] Integrating the above calculations, the virtual heat pool outputs a multi-dimensional vector representing the current thermal state of the system. This vector includes not only the estimated temperature values ​​of key components (such as the engine block, motor windings, and electronic control devices), but also the system's total heat generation rate, total heat dissipation rate, thermal imbalance, the remaining heat dissipation capacity margin of each heat dissipation zone (i.e., how much additional heat can be safely dissipated), and the temperature change trends of key components (such as the rate of heating or cooling). The discrete-time state-space equation of the virtual heat pool is as follows:

[0119]

[0120] in, For state variables, i.e.

[0121] ,

[0122] T i (k) represents the average core coolant temperature (°C) of the i-th heat dissipation zone.

[0123] The natural state coefficient characterizes the natural thermal dynamics of a system without external control or disturbance, i.e., how the temperature of each region evolves naturally over time.

[0124] N For control variables, i.e.

[0125] , Let represent the fan speed corresponding to the i-th heat dissipation area.

[0126] To control the input influence coefficient, the effect of fan speed on heat dissipation is linearized, characterizing the degree of influence of fan speed control input on the temperature of each region.

[0127] U For control variables, i.e.

[0128] , This represents the valve opening degree corresponding to the i-th heat dissipation area.

[0129] To control the input influence coefficient, the effect of valve opening on heat dissipation is linearized, characterizing the degree of influence of valve opening control input on the temperature of each region.

[0130] The perturbation vector, i.e.

[0131] .

[0132] The disturbance coefficient characterizes the degree of influence of heat generation from the heat source on the temperature of each region.

[0133] This thermal state vector provides an accurate and comprehensive system thermal situation map for subsequent prediction and optimization modules, and is the basis for global decision-making.

[0134] Step 4: Energy efficiency decision based on finite-time rolling optimization

[0135] Based on the current detailed thermal state provided by the virtual thermal pool, TMCU initiates a forward-looking, rolling optimization calculation process aimed at achieving global energy efficiency.

[0136] (1) Future heat load forecast

[0137] Combining the future load cycle prediction information received from the VCU (e.g., three consecutive diggings and one rotary unloading will occur within the next 60 seconds), the TMCU inputs the predicted power demand curves of each component into the dynamic estimation model of heat generation power in step three, thereby deriving the heat generation power change curves of each heat source in the same future time period.

[0138] (2) Establishing a rolling optimization problem

[0139] TMCU defines a finite time domain (e.g., the next 60 seconds) as the optimization window. Within this window, the optimization objective is defined as: minimizing the total energy consumed by all cooling accessories, including all lattice fans and coolant circulation pumps, during this time period. The optimization objective function is as follows:

[0140]

[0141] Where J is the objective function value, representing the total energy consumption in the future time domain H;

[0142] H represents the preheating time domain length;

[0143] i represents the unit time step;

[0144] k represents the current time;

[0145] n is the fan index;

[0146] This represents the power consumption of the nth fan at time k+i;

[0147] This represents the power consumption of the nth pump at time k+i;

[0148] This is the weighting factor for the power consumption of the water pump.

[0149] Setting multiple constraints mainly includes:

[0150] a. Safety constraints: Throughout the entire prediction time domain, the predicted temperature of critical components of each engine, drive motor control, and range extender motor control must not exceed their absolute safety limits (e.g., 110°C for the engine and 150°C for the IGBT junction).

[0151] b. Performance Constraints: The temperature of each component should be maintained within its respective high-efficiency operating range as much as possible (e.g., engine coolant 85±5℃, motor and electronic control system 65±5℃) to ensure overall system efficiency.

[0152] 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 (minimum to maximum), and the rate of change must be smooth to avoid abrupt actions.

[0153] 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.

[0154] Advanced strategy decision-making: In optimization problems, the following two strategies are allowed as decision variables to further reduce total power consumption while satisfying constraints:

[0155] Strategy A (Heat Load Transfer): Through controlled bypass of the intelligent integrated valve, a portion of the lower-temperature coolant from a circuit with surplus heat dissipation capacity (resource side) is guided to another high-temperature circuit (demand side) to participate in heat exchange, resulting in lower overall energy consumption. Even if the heat dissipation capacity of the high-temperature circuit itself is not yet saturated, the TMCU will actively divert heat through the integrated valve block. For example, when the ambient temperature is low, even if the drive motor's electronically controlled cooling water pump or cooling fan is not at full load, a portion of the heat from that cooling water circuit will be diverted to the upper intercooling cooling water circuit (where intercooling demand is low and fan efficiency is high) for auxiliary heat dissipation.

[0156] Strategy B (Controllable Heat Storage / Release): This strategy allows certain components with large heat capacity and strong temperature resistance (such as the engine) to temporarily store more heat within a safe temperature range (allowing them to operate under overheating for short periods) to reduce fan energy consumption. When the system enters a low-load phase, the stored heat is dissipated efficiently using coolant or increased airflow. Essentially, this utilizes the components themselves as short-term "heat pools" to smooth out peak heat dissipation power, ensuring the cooling system always operates in a high-efficiency zone.

[0157] (3) Solve and generate the optimal control sequence:

[0158] In each control cycle (e.g., every 10 seconds), TMCU re-solves the above optimization problem based on the latest system state. Using built-in optimization algorithms (such as model predictive control), it calculates a series of optimal control action sequences within the future optimization window.

[0159] TMCU resolves this problem in each control cycle. It simultaneously evaluates the cost of both operating modes:

[0160] Mode 1: Each loop operates completely independently. Each loop uses only its own resources to control the temperature at the setpoint. Calculate the total power consumption P_independent in this mode.

[0161] Mode 2: Enable strategy A and / or B, and calculate the total power consumption P_strategy in this mode. For example, redirect some heat from loop A to loop B (strategy A), or allow loop C to temporarily heat up by 3°C (strategy B).

[0162] Decision principle: Compare the total power consumption P_independent of mode one with the total power consumption P_strategy of mode two.

[0163] If P_strategy is significantly lower than P_independent (e.g., below 5%), then the TMCU output contains the optimal sequence of the corresponding strategy.

[0164] If the two are similar, or P_strategy is even higher (e.g., the valve power consumption caused by the scheduling itself offsets the fan energy saving), the optimizer outputs the optimal sequence for independent operation.

[0165] This action sequence specifies in detail the setpoints for each subsequent shorter control interval (e.g., 1 second), mainly including:

[0166] Fan speed sequence: the future target speeds of the matrix fans of each heat dissipation module in the engine cooling area and the matrix fans of each module in the lower motor and electronic control area.

[0167] 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.

[0168] 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.

[0169] Step 5: Dynamic allocation and execution control.

[0170] 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.

[0171] 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.

[0172] The synthesized final instruction is then converted into specific actuator drive signals:

[0173] a. Fan drive: Generates pulse width modulation (PWM) signals to drive the motor controllers of each dot matrix electronic fan, precisely controlling their speed.

[0174] 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.

[0175] Step Six: Online Self-Learning and Environment Adaptation To achieve continuous optimization and personalization of control strategies, the system possesses online learning capabilities:

[0176] Online self-calibration of model parameters:

[0177] 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.

[0178] Contextualized memory and adaptation of control strategies:

[0179] 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.

[0180] As operational data accumulates, TMCU will create and optimize customized control strategy diagrams for different scenarios. When the current operational scenario is identified as similar to a historical scenario, the corresponding optimized parameters can be quickly invoked or merged to achieve personalized and scenario-specific rapid adaptation of the control strategy.

[0181] Compared with the prior art, the present invention has the following beneficial effects:

[0182] Highly efficient and compact, solving layout challenges: Through a hardware architecture of "independent zoned heat dissipation, evenly distributed matrix fans, and intelligent valve allocation," precise "point-to-point" cooling of each heat source is achieved within the limited engine compartment space of the dual-engine extended-range excavator. This ensures that the drive motor control system, range extender motor control system, and engine all operate within their respective optimal temperature ranges, improving the overall reliability and efficiency of the machine.

[0183] Significant energy-saving effect: The integrated valve block series and parallel water circuit design realizes intelligent thermal energy distribution between cold and heat sources, and the local precise control of the electronic dot matrix fan avoids unnecessary energy consumption.

[0184] Maximizing resource utilization: Through global optimization, the heat dissipation capacity of the entire system is scheduled as a flexible resource pool, breaking through the hardware limitations of physical partitions and realizing the "peak shaving and valley filling" of heat dissipation capacity. Under the premise of meeting the temperature safety constraints of each component, the total power consumption of heat dissipation accessories such as fans and water pumps is minimized, thereby improving the vehicle's range or fuel economy.

[0185] High reliability and redundancy: The multi-zone physical isolation design combined with the software's heat dissipation strategy reconstructs the system's built-in idle heat dissipation capacity, achieving high-performance system-level redundancy and ensuring the reliable operation of the entire machine. Local failures of a single heat dissipation module no longer cause the entire machine to fail and shut down.

[0186] The above description is merely an embodiment of the present invention and does not constitute any limitation on the technical scope of the present invention. Therefore, any minor modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.

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 thermal management 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 electric fan speed sequence, the valve distribution 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 electronic 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 equipped with a one-way proportional valve, and the two one-way proportional valves have opposite conduction directions. Alternatively, the bypass connection device includes a bypass branch connecting the two main channels, and the bypass branch is provided with a directional adjustable bypass check valve.

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; 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, the thermal management control unit uses a dynamic estimation model of heat generation power and, based on real-time speed and torque, queries a pre-stored engine efficiency MAP chart and combines it 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 motors or drive motors, the thermal management control unit uses a dynamic estimation model of heat generation power and, based on real-time collected motor speed, torque, winding temperature, and current and voltage parameters under current operating conditions, combined with pre-stored three-dimensional 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, the thermal management control unit 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. The thermal management control unit has built-in performance models for each heat dissipation module. These performance models are related to coolant flow rate, inlet temperature difference, electric fan speed, and ambient temperature. Based on the current flow rate, inlet temperature, and electric fan speed of each circuit, the unit can predict the instantaneous heat dissipation of each heat dissipation module under the current conditions 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 electric 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, a portion of the lower temperature coolant in a circuit with surplus heat dissipation capacity is 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 thermal management control unit will actively divert heat through the intelligent integrated valve. 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 the energy consumption of the electric fan; 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, the thermal management control unit 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, the thermal management control unit outputs the optimal sequence containing the corresponding strategy; otherwise, the optimizer outputs the optimal sequence for independent operation.

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.

Images