Heating device for vehicle braking system and control method of heating device

Abstract

The invention relates to the technical field of data processing, in particular to a heating device for a vehicle braking system and a control method thereof, and the heating device comprises a split type heating module, a data fusion control module, a partition cooperation module and a self-checking module. The split type heating module is provided with a heat exchange unit linked with a cockpit on a brake assembly of a front vehicle, an aluminum heat preservation bin is constructed on a rear vehicle, a multi-area heat tracing band, a distributed temperature control probe and a mechanical gap sensor are integrated, and initial heat distribution parameters are generated; the data fusion control module constructs a dynamic temperature control model based on hydraulic unit temperature, sealing element deformation and environment temperature data, and global optimization is carried out by combining a genetic algorithm to generate a component zone heating instruction; through multi-source data fusion, dynamic parameter calibration and gradient power reduction mechanisms, the problems of temperature field unbalance and energy consumption redundancy of the split type vehicle body at low temperature are solved, and the braking response speed and the system reliability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a heating device for a vehicle braking system and a control method thereof. Background Art

[0002] The split-type vehicle body braking system is a special braking device for articulated vehicles designed to adapt to low temperatures and complex terrains. Its core feature is that the braking unit and the vehicle body structure adopt a split layout, and the front and rear vehicle bodies are dynamically separated and cooperatively controlled through a flexible connection mechanism. In a low-temperature environment, the system needs to simultaneously cope with physical effects such as the deterioration of the viscosity-temperature characteristics of the brake fluid, the low-temperature embrittlement of the sealing material, and the abnormal clearance caused by the cold shrinkage of metal components. The split structure further exacerbates the difficulty of thermal management.

[0003] In a low-temperature environment, for the braking system of a vehicle with a split-type vehicle body structure, due to the lack of independent cabin heating support for the rear vehicle, the existing temperature control solutions relying on a single heat source or static heat preservation are difficult to achieve multi-region collaborative temperature regulation, resulting in risks of heating lag or local overheating of key components such as hydraulic units, seals, and brake fluid under dynamic working conditions. Specifically, the existing control methods do not establish a closed-loop feedback mechanism for the thermal conduction differences of the split vehicle body and the heat capacity characteristics of components, and cannot dynamically adjust the heating strategy according to real-time data such as the change in brake fluid viscosity, the deformation state of seals, and the mechanical fit clearance, resulting in an unbalanced temperature field distribution and redundant energy consumption, thereby weakening the braking response speed and system reliability in a low-temperature environment. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a heating device for a vehicle braking system and a control method thereof, which are used to solve the problems of insufficient heating area coordination, unbalanced temperature field distribution, and redundant energy consumption caused by the lack of a closed-loop control mechanism based on multi-source sensing data in a split-type vehicle body braking system in a low-temperature environment, so as to improve the braking response speed and system reliability.

[0005] To solve the above technical problems, the specific technical solutions of the present invention are as follows: In a first aspect, the heating device for a vehicle braking system provided by the present invention includes: A split-type heating module, configured to set a first heat exchange unit linked to the hot environment of the driver's cab in the front vehicle braking component, and construct an aluminum thermal insulation bin in the rear vehicle braking system. The aluminum thermal insulation bin integrates multi-region heating tapes, distributed temperature control probes, and mechanical clearance sensors, generates initial thermal distribution parameters, and transmits them to the data fusion control module; The data fusion control module, connected to the split heating module, is used to receive the hydraulic unit temperature data, seal deformation data, and ambient temperature data from the distributed temperature control probes, and access the braking pressure historical parameters of the vehicle bus. Based on the hydraulic unit temperature data, seal deformation data, and ambient temperature data, it constructs a dynamic temperature control model and outputs closed-loop control parameters including the partition heating power command to the partition coordination module; The partition coordination module, connected to the data fusion control module, divides the aluminum thermal insulation bin into a main heating area and an auxiliary heating area, receives the closed-loop control parameters and executes a continuous heating strategy and pulse heating frequency adjustment. The main heating area controls the power output of the heating tape based on the continuous heating strategy, and the auxiliary heating area adjusts the pulse heating frequency according to the real-time feedback data of the mechanical clearance sensor; The self-check module, connected to the partition coordination module, periodically collects the impedance of the heating tape circuit and the calibration deviation data of the temperature control probe. When abnormal impedance or calibration deviation exceeding the limit is detected, it generates abnormal data including the fault area identifier and transmits it to the data fusion control module; Among them, the data fusion control module iteratively optimizes the control parameters of the dynamic temperature control model according to the initial heat distribution parameters and abnormal data, and issues the updated closed-loop control parameters to the partition coordination module, forming a closed-loop control link from data acquisition, model optimization to instruction execution.

[0006] Furthermore, for the heating device used in the vehicle braking system of the present invention, the data fusion control module includes: The genetic algorithm optimization unit is used to generate an initial control parameter set based on the initial temperature field data set of the distributed temperature control probe and the deformation sensor data of the aluminum thermal insulation bin, and transmit it to the model fine-tuning unit; The model fine-tuning unit receives the real-time change amount of the mechanical clearance sensor and the estimated value of the brake fluid viscosity, and online calibrates the initial control parameter set based on the dynamic temperature control model, and outputs the calibrated pulse frequency weight to the pulse heating controller in the auxiliary heating area; The delay compensation unit calls the historical temperature rise curve data stored in the self-check module to predict the thermal inertia delay time, dynamically adjusts the triggering timing of the gradient power reduction mechanism, and issues the adjusted timing instruction to the heating tape drive circuit in the main heating area through the CAN bus; Among them, the pulse frequency weight output by the model fine-tuning unit and the timing instruction of the delay compensation unit together constitute the closed-loop control parameters, driving the partition coordination module to execute the heating strategy.

[0007] Furthermore, for the heating device used in the vehicle braking system of the present invention, the delay compensation unit performs the following operations: When the temperature of the hydraulic unit is lower than the critical threshold, it sends a high-power rapid heating instruction to the heating tape drive circuit in the main heating area; After the temperature reaches the preset safe range, based on the thermal inertia parameters of the dynamic temperature control model, calculate the thermal inertia delay time according to the slope of the historical temperature rise curve, and superimpose the gradient power reduction coefficient to generate a maintenance power command; The maintenance power command, as part of the closed-loop control parameters, is synchronously written into the instruction queue of the partition cooperation module together with the pulse frequency adjustment command of the auxiliary heating zone.

[0008] Furthermore, for the heating device used in the vehicle braking system of the present invention, the model fine-tuning unit includes: A deformation compensation sub-module, based on the deformation amount of the composite heat preservation board of the aluminum heat preservation bin, calls the gap compensation algorithm of the dynamic temperature control model to correct the target temperature setting value of the main heating zone; A viscosity feedback sub-module, which calculates the brake fluid viscosity in real time according to the temperature-viscosity relationship curve, and dynamically adjusts the continuous heating power of the main heating zone and the pulse heating duty cycle of the auxiliary heating zone through fuzzy control rules; Among them, the gap compensation coefficient output by the deformation compensation sub-module and the viscosity adjustment parameter of the viscosity feedback sub-module are jointly input into the genetic algorithm optimization unit as the optimization boundary conditions of the next-generation control parameter set.

[0009] Furthermore, for the heating device used in the vehicle braking system of the present invention, the self-check module includes: An impedance detection unit, which periodically collects the resistance change rate of the heating tape circuit, and when detecting abnormal resistance fluctuations, sends a standby circuit activation command to the partition cooperation module; A deviation calibration unit, which reconstructs the temperature compensation coefficient of the temperature control probe based on historical mean data and writes the reconstructed coefficient into the calibration parameter table of the dynamic temperature control model; A redundant control unit, when detecting that the accuracy of the mechanical clearance sensor exceeds the limit, switches to the heat distribution model based on the front vehicle brake fluid circulation flow data, and feeds back the reconstructed distribution coefficient to the genetic algorithm optimization unit.

[0010] In a second aspect, the heating control method provided by the present invention for a vehicle braking system is applied to a heating device for a vehicle braking system, and includes: Obtain the temperature data of the front vehicle cockpit and the hydraulic unit temperature and seal deformation data collected by the distributed temperature control probes of the aluminum heat preservation bin of the rear vehicle, integrate the data into the initial temperature field data set and input it into the genetic algorithm optimization process; Based on the genetic algorithm, globally optimize the initial temperature field data set, generate an initial control parameter set including a proportional coefficient and an integral time, and transmit it to the parameter calibration interface of the dynamic temperature control model; Based on the real-time mechanical clearance change and the deduced value of the brake fluid viscosity, the initial control parameter set is fine-tuned online through a dynamic temperature control model, and the calibrated pulse frequency weight and continuous heating power command are output to the partition collaborative control queue; The pulse frequency weight is sent to the heating tape circuit in the rear vehicle auxiliary heating area. At the same time, the historical temperature rise curve data stored in the self-check module is called, and the maintenance power of the main heating area is dynamically adjusted based on the gradient power reduction mechanism, and the power distribution parameters of the dynamic temperature control model are updated; When it is detected that the impedance of the heating tape circuit is abnormal or the deviation of the temperature control probe exceeds the limit, it switches to the redundant heating mode and reconstructs the heat distribution coefficient of the dynamic temperature control model based on the front vehicle brake fluid circulation flow data, and feeds back the reconstructed coefficient to the genetic algorithm optimization process as a constraint condition for the next generation of parameter sets.

[0011] Furthermore, the heating control method of the present invention for a vehicle braking system fine-tunes the initial control parameter set online through a dynamic temperature control model based on the real-time mechanical clearance change and the deduced value of the brake fluid viscosity, and outputs the calibrated pulse frequency weight and continuous heating power command to the partition collaborative control queue, including: According to the deformation amount of the composite insulation board of the aluminum insulation bin, the gap compensation algorithm of the dynamic temperature control model is called to dynamically correct the target temperature setting value of the main heating area; Based on the temperature-viscosity relationship curve, the brake fluid viscosity change rate is calculated in real time, and the heating power of the main heating area and the pulse duty cycle of the auxiliary heating area are synchronously adjusted through fuzzy control rules; The corrected target temperature setting value and pulse duty cycle parameters are written into the parameter constraint table of the genetic algorithm optimization unit for updating the next generation of control parameter sets.

[0012] Furthermore, the heating control method of the present invention for a vehicle braking system calculates the brake fluid viscosity change rate in real time based on the temperature-viscosity relationship curve, and synchronously adjusts the heating power of the main heating area and the pulse duty cycle of the auxiliary heating area through fuzzy control rules, including: When the feedback data of the mechanical clearance sensor exceeds the threshold set by the self-check module, a pulse frequency weight increment command is sent to the delay compensation unit; According to the correlation between the brake fluid viscosity change rate and the historical temperature rise curve, the continuous heating power slope of the main heating area is dynamically adjusted and a power reduction command is generated; The adjusted parameters are synchronously sent to the heating tape drive unit through the CAN bus, and the execution log is recorded in the historical database for genetic algorithm iteration.

[0013] Further, for the heating control method of the vehicle braking system of the present invention, when it is detected that the impedance of the heating tape circuit is abnormal or the deviation of the temperature control probe exceeds the limit, it switches to the redundant heating mode and reconstructs the heat distribution coefficient of the dynamic temperature control model based on the front vehicle brake fluid circulation flow data, and feeds the reconstructed coefficient back to the genetic algorithm optimization process as a constraint condition for the next generation parameter set, including: After activating the standby heating tape circuit, calculate the optimal flow rate for transferring heat to the rear vehicle based on the front vehicle brake fluid circulation flow sensor data; According to the optimal flow rate and the deformation sensor data of the aluminum thermal insulation bin, reconstruct the heat loss compensation coefficient of the dynamic temperature control model; Input the reconstructed compensation coefficient into the model fine-tuning process, generate a zoned heating instruction applicable to the fault scenario and write it into the instruction queue.

[0014] Further, the heating control method of the vehicle braking system of the present invention further includes: Periodically collect the resistance change rate data of the heating tape circuit. When it is detected that the sampling values for three consecutive times exceed the tolerance range of the impedance detection unit, trigger the redundant heating mode; In the redundant heating mode, based on the temperature stability parameter of the historical mean data, call the deformation compensation algorithm to reallocate the power ratio between the main heating zone and the auxiliary heating zone; Fuse the reallocated power ratio with the front vehicle brake fluid circulation flow data, generate a new heat distribution instruction and transmit it to the zoned cooperation module through the vehicle-mounted bus.

[0015] Advantages of the present invention; Through the collaborative optimization of multi-source sensing data fusion and the closed-loop control architecture, the present invention effectively solves the thermal management problem of the split vehicle body braking system in low-temperature environments. Based on the real-time data of the distributed temperature control probes and mechanical clearance sensors in the aluminum thermal insulation bin, the dynamic temperature control model combines the clearance compensation algorithm and fuzzy control rules to realize the dynamic correction of the target temperature set value in the main heating zone and the synchronous adjustment of the pulse duty cycle in the auxiliary heating zone, suppressing the loss of heat conduction efficiency caused by the cold shrinkage deformation of the composite insulation board; through the genetic algorithm, globally optimize the initial temperature field data set, generate a control parameter set suitable for low-temperature working conditions, combine the delay compensation unit to predict the thermal inertia delay time, dynamically adjust the triggering timing of the gradient power reduction mechanism, and optimize the zoned heating strategy and energy consumption matching degree; in the redundant heating mode, reconstruct the heat loss compensation coefficient based on the front vehicle brake fluid circulation flow data, and generate a zoned heating instruction in combination with the feedback of the deformation sensor to improve the temperature field stability in the fault scenario; the self-check module periodically collects the loop impedance and probe deviation data, and forms a closed-loop control link from anomaly detection, model reconstruction to genetic algorithm optimization through the iterative feedback mechanism of the historical database and parameter constraint table, enhancing the anti-interference ability and long-term operation reliability of the system in complex low-temperature environments. Brief Description of the Drawings

[0016] To more clearly illustrate the technical solutions of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0017] Figure 1 It is a flowchart of a control method for a heating device used in a vehicle braking system provided by an embodiment of the present invention.

[0018] Figure 2 It is a schematic external view of an aluminum thermal insulation bin of a control method for a heating device used in a vehicle braking system provided by an embodiment of the present invention. Detailed Embodiments

[0019] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention. The technical solutions provided by each embodiment of the present invention will be described in detail below with reference to the drawings. To better understand the objectives of the present invention, the present invention will be further described in detail below.

[0020] In a first aspect, the heating device for a vehicle braking system provided by the present invention includes: A split heating module configured to set a first heat exchange unit linked to the hot environment of the driver's cab in the front vehicle braking assembly, and construct an aluminum thermal insulation bin in the rear vehicle braking system. The aluminum thermal insulation bin integrates multi-zone heating tapes, distributed temperature control probes and mechanical clearance sensors to generate initial thermal distribution parameters and transmit them to the data fusion control module; A data fusion control module, connected to the split heating module, for receiving hydraulic unit temperature data, seal deformation data and ambient temperature data from the distributed temperature control probes, and accessing the braking pressure historical parameters of the vehicle-mounted bus. Based on the hydraulic unit temperature data, seal deformation data and ambient temperature data, a dynamic temperature control model is constructed, and closed-loop control parameters including zonal heating power instructions are output to the zonal coordination module; A zonal coordination module, connected to the data fusion control module, divides the aluminum thermal insulation bin into a main heating zone and an auxiliary heating zone, receives the closed-loop control parameters and executes a continuous heating strategy and pulse heating frequency adjustment. The main heating zone controls the power output of the heating tape based on the continuous heating strategy, and the auxiliary heating zone adjusts the pulse heating frequency according to the real-time feedback data of the mechanical clearance sensor; The self-check module, connected to the partition cooperation module, periodically collects the impedance data of the tracing heating cable loop and the calibration deviation data of the temperature control probe. When abnormal impedance or calibration deviation exceeding the limit is detected, it generates abnormal data including the fault area identifier and transmits it to the data fusion control module; Among them, the data fusion control module iteratively optimizes the control parameters of the dynamic temperature control model according to the initial heat distribution parameters and the abnormal data, and sends the updated closed-loop control parameters to the partition cooperation module, forming a closed-loop control link from data acquisition, model optimization to instruction execution.

[0021] Specifically, for the heating device used in the vehicle braking system of the present invention, the data fusion control module includes: The genetic algorithm optimization unit is used to generate an initial control parameter set based on the initial temperature field data set of the distributed temperature control probe and the deformation sensor data of the aluminum thermal insulation bin, and transmit it to the model fine-tuning unit; The model fine-tuning unit receives the real-time change of the mechanical clearance sensor and the estimated value of the brake fluid viscosity, and online calibrates the initial control parameter set based on the dynamic temperature control model, and outputs the calibrated pulse frequency weight to the pulse heating controller in the auxiliary heating area; The delay compensation unit calls the historical temperature rise curve data stored in the self-check module to predict the thermal inertia delay time, dynamically adjusts the trigger timing of the gradient power reduction mechanism, and sends the adjusted timing instruction to the tracing heating cable drive loop in the main heating area through the CAN bus; Among them, the pulse frequency weight output by the model fine-tuning unit and the timing instruction of the delay compensation unit together constitute the closed-loop control parameters, driving the partition cooperation module to execute the heating strategy.

[0022] Specifically, for the heating device used in the vehicle braking system of the present invention, the delay compensation unit performs the following operations: When the temperature of the hydraulic unit is lower than the critical threshold, it sends a high-power rapid heating instruction to the tracing heating cable drive loop in the main heating area; After the temperature reaches the preset safe range, based on the thermal inertia parameters of the dynamic temperature control model, calculate the thermal inertia delay time according to the slope of the historical temperature rise curve, and generate a maintenance power instruction by superimposing the gradient power reduction coefficient; The maintenance power instruction, as a part of the closed-loop control parameters, is synchronously written into the instruction queue of the partition cooperation module together with the pulse frequency adjustment instruction in the auxiliary heating area.

[0023] Specifically, for the heating device used in the vehicle braking system of the present invention, the model fine-tuning unit includes: The deformation compensation sub-module, based on the deformation of the composite insulation board of the aluminum thermal insulation bin, calls the gap compensation algorithm of the dynamic temperature control model to correct the target temperature setting value in the main heating area; A viscosity feedback sub-module calculates the brake fluid viscosity in real time according to the temperature-viscosity relationship curve, and dynamically adjusts the continuous heating power of the main heating zone and the pulse heating duty cycle of the auxiliary heating zone through fuzzy control rules; Among them, the gap compensation coefficient output by the deformation compensation sub-module and the viscosity adjustment parameter of the viscosity feedback sub-module are jointly input into the genetic algorithm optimization unit as the optimization boundary conditions for the next generation of control parameter sets.

[0024] Specifically, for the heating device used in the vehicle braking system of the present invention, the self-check module includes: An impedance detection unit periodically collects the resistance change rate of the heating tape circuit, and when an abnormal resistance fluctuation is detected, it sends a standby circuit activation instruction to the partition cooperation module; A deviation calibration unit reconstructs the temperature compensation coefficient of the temperature control probe based on historical mean data and writes the reconstructed coefficient into the calibration parameter table of the dynamic temperature control model; A redundant control unit switches to a heat distribution model based on the front vehicle brake fluid circulation flow data when the accuracy of the mechanical gap sensor is detected to be exceeded, and feeds back the reconstructed distribution coefficient to the genetic algorithm optimization unit.

[0025] Please refer to Figure 1 Secondly, the heating control method for a vehicle braking system provided by the present invention is applied to a heating device for a vehicle braking system, and includes: Step S101: Obtain the front vehicle cockpit temperature data and the hydraulic unit temperature and seal deformation data collected by the distributed temperature control probes in the rear vehicle aluminum thermal insulation bin, integrate the data into an initial temperature field data set, and input it into the genetic algorithm optimization process; In the heating control method of the present invention, in step S101, through the collaborative acquisition and preprocessing of multi-source sensing data, reliable input conditions are provided for the genetic algorithm optimization. The front vehicle cockpit temperature data is collected in real time by a temperature sensor integrated at the air outlet of the cockpit air conditioner. The sensor measures the air temperature using the thermocouple principle, and the data is transmitted to the rear vehicle control module through the in-vehicle bus. The distributed temperature control probes arranged in the rear vehicle aluminum thermal insulation bin are installed in layers along the hydraulic unit pipeline, seal installation position, and brake disc surface. The platinum resistance temperature sensor is used to collect the surface temperature of the hydraulic unit, and the strain gauge sensor is used to monitor the deformation displacement of the seal. The data sampling frequency is dynamically adjusted according to the change of the braking pressure.

[0026] After the multi-source data collected are aligned by time stamps and processed by noise filtering, they are integrated into an initial temperature field data set. The time stamp alignment module uses a GPS synchronous clock signal to achieve the temporal consistency of the data of the vehicle ahead and the vehicle behind; the noise filtering eliminates the signal jumps caused by environmental electromagnetic interference through a moving window mean algorithm. The integrated data set includes a spatial temperature distribution matrix, a deformation displacement vector, and an environmental temperature scalar, which are mapped into a three-dimensional temperature field model as the input conditions of the physical field optimized by the genetic algorithm. After the data set is converted through a standardized format, it is written into the data buffer queue of the genetic algorithm optimization unit to complete the unified interface adaptation of multi-source heterogeneous data.

[0027] The construction logic of the initial temperature field data set supports the subsequent optimization of control parameters. The temperature data of the driver's cockpit of the vehicle ahead reflects the heat source input efficiency of the heat exchange unit, and the temperature data of the hydraulic unit of the vehicle behind and the deformation data of the seal represent the real-time heat load state of the braking system. The data integration process fills the blind area covered by sensors through a spatial interpolation algorithm. For example, the Kriging interpolation method is used to generate the temperature estimation values of the area inside the aluminum thermal insulation bin where no probes are arranged. When the integrated data set is input into the genetic algorithm optimization process, the algorithm calls the key node data in the temperature field model to generate an initial control parameter set suitable for low-temperature scenarios, providing benchmark parameters for the online calibration of the dynamic temperature control model.

[0028] The above steps form a technical closed-loop through hierarchical processing of data acquisition, preprocessing, and model input: the multi-sensor layout solves the problem of spatial coverage of the split vehicle body, data integration eliminates the differences in heterogeneous data, and the temperature field model provides physical constraints for algorithm optimization. The data flow and instruction flow between each link cooperate through the in-vehicle bus and the data buffer queue, enabling the genetic algorithm to generate a globally optimal control strategy based on real working condition data, laying a foundation for subsequent zonal heating control.

[0029] Step S102: Perform global optimization on the initial temperature field data set based on the genetic algorithm, generate an initial control parameter set including a proportional coefficient and an integral time, and transmit it to the parameter calibration interface of the dynamic temperature control model; In the heating control method of the present invention, step S102 generates an initial control strategy suitable for low-temperature scenarios through the global optimization and parameter adaptation mechanism of the genetic algorithm. After receiving the initial temperature field data set, the genetic algorithm optimization unit constructs a multi-objective fitness function to comprehensively evaluate the indicators of temperature uniformity, energy consumption efficiency, and response speed. The fitness function maps the spatial temperature distribution matrix in the temperature field data set into a heat conduction efficiency score, converts the seal deformation displacement data into a mechanical stability weight, and uses the environmental temperature scalar as a heat loss correction factor to form a multi-dimensional optimization target space. The algorithm selects the parent parameter combination through the roulette wheel selection strategy, performs crossover and mutation operations to generate a new generation of parameter sets, and iteratively optimizes until the fitness score converges.

[0030] The generated initial control parameter set includes a proportional coefficient, an integral time, and a fuzzy rule weight, corresponding to the error adjustment rate, the cumulative deviation compensation amount, and the non - linear control threshold in the dynamic temperature control model respectively. The parameter set is encapsulated with data through a standardized format conversion module to match the parameter calibration interface protocol of the dynamic temperature control model. The calibration interface adopts a two - way verification mechanism to verify the compatibility between the parameter value range and the model input constraint conditions. For example, the proportional coefficient shall not exceed the maximum thermal stress threshold of the aluminum thermal insulation bin material. After passing the verification, the parameter set is written into the parameter storage area of the dynamic temperature control model through a high - speed data bus to complete the data docking between the algorithm layer and the model layer.

[0031] During the parameter transmission process, the calibration interface synchronously generates metadata tags to record the optimized version of the parameter set, the timestamp, and the associated temperature field characteristics. The metadata is transmitted to the historical database of the self - inspection module through the vehicle - mounted bus as a reference benchmark for subsequent model fine - tuning and anomaly diagnosis. The global optimization result of the initial control parameter set provides a reference input for the dynamic temperature control model, enabling the model to quickly start online calibration based on real - time working condition data, reducing the control lag in the cold - start phase, and improving the thermal management response efficiency of the braking system at low temperatures.

[0032] The above steps form a technical closed - loop through a three - level processing mechanism of objective function construction, parameter optimization, and interface adaptation: the temperature field data drives the algorithm optimization, the parameter set encapsulation realizes model compatibility, and the metadata record supports iterative traceability. Each link relies on the collaborative architecture of the genetic algorithm and the dynamic temperature control model to solve the problem of initializing the control parameters of the split - body vehicle body during the initial heating stage, providing an optimized starting point for multi - region collaborative heating.

[0033] Step S103: According to the real - time mechanical clearance change amount and the estimated value of the brake fluid viscosity, the initial control parameter set is fine - tuned online through the dynamic temperature control model, and the calibrated pulse frequency weight and continuous heating power command are output to the partition collaborative control queue; In the heating control method of the present invention, in step S103, the initial control parameters are calibrated in real time through the dynamic temperature control model to achieve dynamic matching between the heating strategy and the working condition changes. The real - time mechanical clearance change amount is collected by distributed mechanical clearance sensors in the aluminum thermal insulation bin. The sensors measure the clearance increment caused by the cold shrinkage deformation of the composite insulation board based on the Hall effect principle. After the data is filtered by Kalman filter to eliminate measurement noise, it is input into the dynamic temperature control model. The estimated value of the brake fluid viscosity is calculated in real time through the temperature - viscosity relationship curve. Combining the temperature feedback data of the main heating area, a polynomial fitting algorithm is used to generate the viscosity change rate curve, which is used as the input parameter for model fine - tuning.

[0034] During the dynamic temperature control model call, the gap compensation algorithm and fuzzy control rules are executed for online fine-tuning. The gap compensation algorithm dynamically corrects the target temperature setting value of the main heating zone according to the mapping relationship between the deformation of the composite insulation board and the heat conduction efficiency. For example, when the deformation increases by 0.5 mm, the target temperature is increased by 1.5 °C to compensate for heat loss. The fuzzy control rules divide the viscosity change rate into three control domains of "low-medium-high", and adjust the rising slope of the continuous heating power in the main heating zone according to the preset fuzzy inference table. At the same time, the pulse duty cycle of the auxiliary heating zone is adjusted proportionally and synchronously to prevent the seal from overheating and deforming due to sudden viscosity changes. The calibrated pulse frequency weight and continuous power command are converted into a standardized control command through the data encapsulation module and written into the partitioned cooperative control queue according to the priority.

[0035] During the calibration process, the corrected target temperature setting value and pulse duty cycle parameter are synchronously written into the parameter constraint table of the genetic algorithm optimization unit. The constraint table records the correlation between the current control parameters and the temperature field distribution. For example, when the temperature fluctuation in the main heating zone exceeds ±2 °C, the constraint table automatically limits the maximum adjustment range of the pulse duty cycle to ±15%. Based on the boundary conditions in the constraint table, the genetic algorithm recalculates the combination of the proportional coefficient and integral time in the next-generation parameter optimization, forming a technical closed-loop from model fine-tuning to algorithm iteration. The calibrated control command is sent to the heating tape drive unit of the rear vehicle auxiliary heating zone in real time through the CAN bus, and at the same time, the execution status log is encrypted and stored in the historical database to provide data support for redundant control and parameter optimization.

[0036] The above steps achieve the precise generation of the zoned heating instruction through the multi-level cooperation of sensor data acquisition, model algorithm call, and parameter constraint update. The mechanical gap deformation data drives the temperature compensation logic, the viscosity change rate triggers the fuzzy control strategy, and the parameter constraint mechanism ensures the stability of the control command, ultimately solving the heating lag and energy consumption redundancy problems of the split braking system at low temperatures.

[0037] Step S104: Send the pulse frequency weight to the heating tape circuit of the rear vehicle auxiliary heating zone, and at the same time call the historical temperature rise curve data stored in the self-check module, dynamically adjust the maintenance power of the main heating zone based on the gradient power reduction mechanism, and update the power distribution parameters of the dynamic temperature control model; In the heating control method of the present invention, step S104 realizes the dynamic optimization of the zoned heating strategy through the cooperation mechanism of instruction sending and power adjustment. The pulse frequency weight is encapsulated into a control instruction packet through the CAN bus protocol. The instruction packet includes area coding, frequency value, and timestamp information, and is transmitted to the heating tape drive unit of the rear vehicle auxiliary heating zone after being sorted according to the priority. After the drive unit analyzes the instruction packet, it adjusts the working frequency of the heating tape according to the preset pulse waveform template. For example, the weight value is mapped to a pulse signal of 0.5 Hz to 5 Hz to match the real-time feedback rhythm of the mechanical gap sensor and suppress the risk of local overheating caused by gap deformation.

[0038] When the self-check module calls the historical temperature rise curve data, it uses a sliding window algorithm to extract the average temperature rise rate within the most recent 30 minutes. Combining with the measured value of the current main heating zone temperature, it calculates the adjustment slope of the maintenance power through a gradient power reduction mechanism. The gradient power reduction mechanism is based on a thermal inertia delay time prediction model. For example, when the average temperature rise rate is lower than 80% of the historical peak, the heating power is gradually reduced at a gradient of 0.2 °C / min, and at the same time, the adjusted slope value is written into the power distribution parameter table of the dynamic temperature control model. After the parameter table is updated, the model recalculates the power distribution weights between the main heating zone and the auxiliary heating zone, generates a new instruction queue and overwrites the old parameters to avoid the control instruction failure caused by parameter conflicts.

[0039] After the updated power distribution parameters are verified for logical consistency by the data verification module, they are synchronized to the historical database of the genetic algorithm optimization unit. The database records the parameter version number, update timestamp, and associated temperature field characteristics, serving as a reference benchmark for subsequent redundant control or parameter iteration. The adjustment result of the maintenance power in the main heating zone is real-time fed back to the self-check module, triggering the dynamic refresh of the temperature rise curve data and forming a closed-loop link from instruction execution to data update. The above steps solve the problem of energy consumption redundancy in the continuous heating stage of the split body vehicle through hierarchical processing of instruction issuance, power adjustment, and parameter refresh, improving the stability and energy efficiency ratio of temperature field control.

[0040] Step S105, when the impedance of the tracing heating cable loop or the deviation of the temperature control probe exceeds the limit, switch to the redundant heating mode and reconstruct the heat distribution coefficient of the dynamic temperature control model based on the front vehicle brake fluid circulation flow data, and feed back the reconstructed coefficient to the genetic algorithm optimization process as a constraint condition for the next generation of parameter sets.

[0041] In the heating control method of the present invention, step S105 solves the problem of thermal management fault tolerance control of the split body vehicle braking system through the redundant heating mode and the dynamic parameter reconstruction mechanism. When the self-check module detects that the impedance of the tracing heating cable loop or the calibration deviation of the temperature control probe exceeds the preset threshold, the redundant control unit immediately triggers the hardware switching logic: the standby tracing heating cable loop is activated through the relay control circuit, and at the same time, the real-time data of the front vehicle brake fluid circulation flow sensor is read. The flow sensor uses a turbine flowmeter to collect the flow velocity information, and the data is input into the heat distribution model after being processed by the sliding window filter to calculate the optimal flow velocity for transferring heat to the rear vehicle. The calculation of the optimal flow velocity combines the heat loss coefficient in the historical fault scenario. For example, when the flow velocity exceeds the safety threshold, the heat transfer rate is automatically limited to avoid the thermal stress of the brake fluid pipeline from exceeding the limit.

[0042] When reconstructing the heat distribution coefficient of the dynamic temperature control model, the system synchronously calls the cold shrinkage deformation data collected by the deformation sensor of the aluminum thermal insulation bin. The deformation data and the optimal flow rate are jointly analyzed through the thermodynamics coupling model to calculate the influence weight of the composite thermal insulation board deformation on the heat conduction path. The model dynamically corrects the gradient parameter of the heat loss compensation coefficient based on the influence weight. For example, when the deformation increases by 1 mm, the compensation coefficient is increased by 0.3% to offset the heat efficiency loss caused by structural deformation. The corrected compensation coefficient is written into the fine-tuning module of the dynamic temperature control model through the model interface to replace the original parameter set in the fault area and generate a zone heating instruction applicable to the current abnormal scenario.

[0043] The generated instructions are encoded according to the priority and written into the instruction queue. The high-priority instructions are sent to the heating tape drive unit in real time through the CAN bus, and the low-priority instructions are temporarily stored in the buffer queue and executed in batches according to the temperature control requirements. During the execution process, the temperature response data and the energy consumption index are synchronously recorded in the historical database and converted into the constraint condition parameters of the genetic algorithm optimization unit through the feature extraction module. The constraint condition parameters limit the search boundary of the next-generation control parameter set. For example, the adjustment range of the main heating zone power is limited within the safety threshold of the fault scenario. The reconstructed heat distribution coefficient and the historical data jointly form the input conditions for the algorithm iteration, forming a closed-loop control link from abnormal response to parameter optimization, and improving the robustness and temperature stability of the system under low-temperature conditions.

[0044] The above steps form a technical closed-loop through hierarchical processing of anomaly detection, model reconstruction, and instruction execution: hardware switching ensures the basic heating function, parameter reconstruction optimizes the heat distribution strategy, and data feedback drives the algorithm iteration. Each link relies on the data fusion center of the dynamic temperature control model to achieve cross-module collaboration, solves the problems of temperature field out-of-control and energy consumption imbalance in the fault scenario of the existing solution, and enhances the fault tolerance and long-term reliability of the split braking system.

[0045] The heating control method for a vehicle braking system provided by the present invention realizes precise temperature control of the split vehicle body braking system through a multi-source data fusion and closed-loop control mechanism. The specific implementation process is as follows: First, the surface temperature of the hydraulic unit, the deformation displacement of the seal, and the change value of the mechanical clearance are collected in real time through the temperature sensor in the front cockpit and the distributed temperature control probes in the aluminum thermal insulation bin of the rear vehicle. These data are integrated into an initial temperature field data set as the input condition for genetic algorithm optimization after timestamp alignment and noise filtering processing. The initial data set includes the spatial temperature distribution characteristics and deformation correlation parameters, providing physical field boundary constraints for subsequent global optimization.

[0046] When globally optimizing the initial temperature field dataset based on the genetic algorithm, a multi-objective fitness function is used to evaluate the temperature control efficiency of different combinations of control parameters. The fitness function comprehensively considers the temperature uniformity, energy consumption efficiency, and response speed indicators, and generates an initial set of control parameters including the proportional coefficient, integral time, and fuzzy rule weights through crossover and mutation operations. The optimized parameter set is transmitted to the parameter calibration interface of the dynamic temperature control model via the vehicle bus to complete the data docking between the algorithm layer and the model layer.

[0047] After receiving the real-time mechanical clearance sensor data and the estimated value of the brake fluid viscosity, the dynamic temperature control model starts the online fine-tuning process. The model calls the clearance compensation algorithm to dynamically correct the target temperature setting value of the main heating zone according to the deformation of the composite insulation board of the aluminum thermal insulation bin; at the same time, based on the temperature-viscosity relationship curve, the continuous heating power of the main heating zone and the pulse duty ratio of the auxiliary heating zone are synchronously adjusted through fuzzy control rules. The calibrated pulse frequency weight and the continuous heating power command are written into the partition cooperative control queue to match the instruction issuing timing and execution priority.

[0048] During the instruction execution stage, the pulse frequency weight is sent to the heating tape drive unit of the auxiliary heating zone of the rear vehicle via the CAN bus to trigger the adjustment of the pulse heating frequency. The maintenance power of the main heating zone is dynamically adjusted based on the historical temperature rise curve data stored in the self-check module: adopting a gradient power reduction mechanism, gradually reducing the heating power slope according to the predicted result of the temperature rise rate to avoid temperature overshoot. The dynamic temperature control model synchronously updates the power distribution parameters and feeds back the actual temperature control effect to the genetic algorithm optimization unit to form the basis for parameter iteration.

[0049] When the self-check module detects an abnormal impedance in the heating tape circuit or an excessive calibration deviation of the temperature control probe, the system switches to the redundant heating mode. In this mode, the optimal heat transfer flow rate is calculated based on the data of the brake fluid circulation flow sensor of the front vehicle, and the heat loss compensation coefficient of the dynamic temperature control model is reconstructed in combination with the feedback of the aluminum thermal insulation bin deformation sensor. The reconstructed compensation coefficient is input into the model fine-tuning process to generate partition heating instructions applicable to the fault scenario, and is sent to the corresponding heating area through the instruction queue. The temperature stability data generated during the redundant control process is synchronously written into the historical database to optimize the robustness boundary conditions of the next generation of control parameter sets.

[0050] A closed-loop interaction is formed between each step through the data bus and control instructions: the initial data collection provides input for algorithm optimization, the model fine-tuning results drive the operations of the execution layer, the abnormal detection data triggers redundant control, and finally feedbacks to the parameter iteration process. This hierarchical control architecture from data fusion, model optimization to execution feedback effectively solves the problem of thermal management coordination of split-body vehicles at low temperatures and improves the system reliability and energy efficiency ratio.

[0051] Specifically, the heating control method for a vehicle braking system according to the present invention performs online fine-tuning of the initial control parameter set through a dynamic temperature control model based on the real-time mechanical clearance change amount and the estimated value of the brake fluid viscosity, and outputs the calibrated pulse frequency weight and the continuous heating power command to the partition collaborative control queue, including: According to the deformation amount of the composite insulation board of the aluminum insulation bin, the target temperature setting value of the main heating area is dynamically corrected by invoking the clearance compensation algorithm of the dynamic temperature control model; Based on the temperature-viscosity relationship curve, the brake fluid viscosity change rate is calculated in real time, and the heating power of the main heating area and the pulse duty ratio of the auxiliary heating area are synchronously adjusted through fuzzy control rules; The corrected target temperature setting value and the pulse duty ratio parameter are written into the parameter constraint table of the genetic algorithm optimization unit for updating the next-generation control parameter set.

[0052] In the heating control method for a vehicle braking system according to the present invention, the online fine-tuning process of the dynamic temperature control model realizes precise temperature control through multi-dimensional parameter collaborative optimization. During specific implementation, the mechanical clearance change amount generated by the low-temperature deformation of the composite insulation board of the aluminum insulation bin is collected in real time by a distributed sensor and input into the clearance compensation algorithm of the dynamic temperature control model. Based on the mapping relationship between the deformation amount and the heat conduction efficiency, the algorithm dynamically corrects the target temperature setting value of the main heating area. For example, when the clearance of the composite insulation board expands due to cold shrinkage, the target temperature is automatically increased to compensate for heat loss and maintain the temperature balance of the hydraulic unit and the brake fluid pipeline.

[0053] The estimated value of the brake fluid viscosity is calculated in real time through the temperature-viscosity relationship curve. Combining with the temperature feedback data of the main heating area, the fuzzy control rules are triggered to jointly adjust the heating power and the pulse duty ratio. The fuzzy controller divides control domains such as "low viscosity - rapid temperature rise" and "high viscosity - slow release heating" according to the viscosity deviation magnitude and change trend, dynamically adjusts the output slope of the continuous heating power of the main heating area, and simultaneously synchronously adjusts the pulse duty ratio of the auxiliary heating area according to a preset ratio to avoid the aggravation of the deformation of the seal due to local overheating. The adjusted parameters are written into the partition collaborative control queue through the in-vehicle bus and are batch-executed after being sorted according to the instruction priority.

[0054] After being verified, the corrected target temperature setting value and the pulse duty ratio parameter are written into the parameter constraint table of the genetic algorithm optimization unit. The constraint table records the correlation between the current control parameters and the temperature field distribution, serving as the optimization boundary condition for the next-generation control parameter set. For example, when the temperature fluctuation in the main heating area exceeds the preset threshold, the constraint table automatically limits the maximum adjustment amplitude of the pulse duty ratio to prevent system oscillation caused by excessive correction. Based on the boundary conditions in the constraint table, the genetic algorithm recalculates the optimal combination of the proportional coefficient and the integral time, iteratively generates an updated parameter set suitable for low-temperature scenarios, and completes the closed-loop control from model fine-tuning to algorithm optimization.

[0055] The above steps form a technical closed-loop through the hierarchical transmission of data flow and control instructions: the mechanical clearance data drives temperature compensation, the viscosity change triggers fuzzy control, and the result of parameter correction feeds back to optimize the genetic algorithm. The data interaction between each link is uniformly scheduled by the dynamic temperature control model to achieve the dynamic balance between the sub-region heating strategy and the global energy consumption target, and solve the contradiction problems of temperature lag and local overheating in the existing solutions.

[0056] Specifically, the heating control method of the present invention for a vehicle braking system calculates the viscosity change rate of the brake fluid in real time based on the temperature-viscosity relationship curve, and synchronously adjusts the heating power of the main heating zone and the pulse duty ratio of the auxiliary heating zone through fuzzy control rules, including: When the feedback data of the mechanical clearance sensor exceeds the threshold set by the self-check module, a pulse frequency weight increment instruction is sent to the delay compensation unit; According to the correlation between the viscosity change rate of the brake fluid and the historical temperature rise curve, the continuous heating power slope of the main heating zone is dynamically adjusted and a power reduction instruction is generated; The adjusted parameters are synchronously sent to the heating tape drive unit through the CAN bus, and the execution log is recorded in the historical database for genetic algorithm iteration.

[0057] In the heating control method of the present invention, the fuzzy control strategy based on the temperature-viscosity relationship curve realizes the dynamic optimization of heating parameters through multi-source data collaboration. When the mechanical clearance sensor detects that the mating clearance value exceeds the deformation threshold preset by the self-check module, the system automatically triggers an abnormal response mechanism: the self-check module calls the clearance safety range data in the historical working condition database, compares the deviation rate between the current clearance increment and the preset threshold, generates a pulse frequency weight increment instruction and transmits it to the delay compensation unit through the control bus. This threshold is dynamically set according to the thermal expansion coefficient of the aluminum thermal insulation bin material and historical deformation data to avoid the risk of mechanical interference caused by low-temperature embrittlement.

[0058] The viscosity change rate of the brake fluid is calculated by fitting the real-time data collected by the temperature sensor with the temperature-viscosity relationship curve, and combining the same working condition records in the historical temperature rise curve database, the correlation between the viscosity change trend and the temperature rise rate is analyzed. When it is detected that the viscosity decrease rate exceeds the historical average value, the dynamic temperature control model starts a power reduction protection mechanism: based on the viscosity-power mapping table in the fuzzy control rules, the rising slope of the continuous heating power of the main heating zone is reduced according to a preset gradient, and the adjusted slope value is written into the power reduction instruction queue. The trigger threshold of the power reduction instruction is associated with the standard deviation of the historical temperature rise curve to prevent misregulation caused by sudden viscosity fluctuations.

[0059] The adjusted heating power parameters and pulse frequency weights are packed into a control instruction set through the CAN bus protocol and synchronously sent to the heating tape drive units in the main heating zone and the auxiliary heating zone in the order of priority. The instruction set includes a timestamp identifier and a zone code to achieve precise timing control of multi-zone heaters to match the rhythm of mechanical clearance changes. The temperature response data, energy consumption indicators, and instruction execution status during the execution process generate an operation log, which is encrypted and stored in the historical database according to the time series. The log data is converted into optimization parameters recognizable by the genetic algorithm through a feature extraction module and used for the fitness function calculation of the next-generation control parameter set, realizing a data closed-loop from execution feedback to algorithm iteration.

[0060] The above steps form a technical closed-loop through a three-level processing mechanism of exception response, trend analysis, and data recording: the clearance anomaly triggers an immediate control instruction, the viscosity trend analysis drives the power protection strategy, and the execution data feeds back to optimize the algorithm. Each link relies on the data scheduling center of the dynamic temperature control model to achieve instruction coordination, solve the problem of mismatch between mechanical deformation and thermal management response in the existing solutions, and improve the thermal stability and control accuracy of the braking system at low temperatures.

[0061] Specifically, for the heating control method of the vehicle braking system of the present invention, when it is detected that the impedance of the heating tape circuit is abnormal or the deviation of the temperature control probe exceeds the limit, it switches to the redundant heating mode and reconstructs the heat distribution coefficient of the dynamic temperature control model based on the front vehicle's brake fluid circulation flow data. The reconstructed coefficient is fed back to the genetic algorithm optimization process as a constraint condition for the next-generation parameter set, including: After activating the standby heating tape circuit, calculate the optimal flow rate for transferring heat to the rear vehicle based on the front vehicle's brake fluid circulation flow sensor data; According to the optimal flow rate and the deformation sensor data of the aluminum thermal insulation bin, reconstruct the heat loss compensation coefficient of the dynamic temperature control model; Input the reconstructed compensation coefficient into the model fine-tuning process, generate a zone heating instruction applicable to the fault scenario, and write it into the instruction queue.

[0062] In the heating control method of the present invention, the switching of the redundant heating mode and the reconstruction of the dynamic temperature control model are realized through multi-source data linkage to achieve thermal management fault tolerance control in the fault scenario. When the self-check module detects that the impedance of the heating tape circuit is abnormal or the calibration deviation of the temperature control probe exceeds the preset safety range, the redundant control module immediately triggers the hardware switching logic of the standby heating tape circuit. The activation instruction of the standby circuit is sent to the drive unit of the rear vehicle's aluminum thermal insulation bin through the redundant control bus, and at the same time, the real-time flow rate data of the front vehicle's brake fluid circulation flow sensor is read, and the optimal flow rate for transferring heat to the rear vehicle is calculated based on the flow-heat transfer efficiency model. The calculation process of the optimal flow rate combines the heat loss coefficient in the historical fault scenario to avoid the thermal stress of the brake fluid circulation pipeline exceeding the limit due to too high a flow rate.

[0063] When reconstructing the heat loss compensation coefficient of the dynamic temperature control model, the system synchronously calls the data of the cold shrinkage deformation amount of the silo collected by the deformation sensor of the aluminum thermal insulation silo. The deformation amount data and the optimal flow rate are coupled and calculated through the thermodynamic simulation model to analyze the influence weight of the deformation of the composite thermal insulation board on the heat conduction path, and the gradient parameter of the heat loss compensation coefficient is dynamically corrected. The corrected compensation coefficient is input into the fine-tuning module of the dynamic temperature control model through the model interface to replace the original parameter set in the fault area. Based on the matching degree between the compensation coefficient and the current temperature field distribution data, the fine-tuning module generates a zoned heating instruction applicable to the fault scenario. The instruction includes the power reduction slope limit of the main heating area and the pulse frequency safety threshold of the auxiliary heating area.

[0064] The generated zoned heating instructions are encoded and written into the instruction queue according to the priority. The queue management module sorts them according to the instruction type and execution urgency. High-priority instructions are sent to the heating tape drive unit in real time through the CAN bus, and low-priority instructions are temporarily stored in the buffer queue and wait for the execution window. The temperature response data and energy consumption indicators generated during the instruction execution process are synchronously recorded in the historical database, and after feature extraction, the data is converted into the constraint condition parameters of the genetic algorithm optimization unit. The constraint condition parameters are used to limit the search space of the next-generation control parameter set. For example, the power adjustment range of the main heating area is limited not to exceed the safety threshold in the fault scenario, so as to improve the stability of the redundant control process.

[0065] The above steps form a technical closed-loop through a three-level fault tolerance mechanism of hardware switching, model reconstruction, and instruction scheduling: fault detection triggers the activation of the standby loop and data reconstruction, model fine-tuning generates a safe heating strategy, and execution feedback optimizes the parameter boundaries of the algorithm. Each link relies on the data fusion center of the dynamic temperature control model to achieve cross-module collaboration, solves the problem of temperature field out-of-control in the fault scenario of the existing solution, and enhances the robustness of the split braking system in low-temperature environments.

[0066] Specifically, the heating control method for a vehicle braking system of the present invention further includes: Periodically collect the resistance change rate data of the heating tape circuit. When it is detected that the sampling values for three consecutive times exceed the tolerance range of the impedance detection unit, trigger the redundant heating mode; In the redundant heating mode, based on the temperature stability parameters of the historical mean data, call the deformation compensation algorithm to reallocate the power ratio between the main heating area and the auxiliary heating area; Fuse the reallocated power ratio with the front vehicle brake fluid circulation flow rate data, generate a new heat distribution instruction and transmit it to the zoned collaboration module through the vehicle bus.

[0067] In the heating control method of the present invention, the triggering of the redundant heating mode and the optimization of power distribution are realized through the cooperation of multi-source data to achieve thermal management self-adaptation under abnormal conditions. When periodically collecting the data of the change rate of the resistance of the heating tape circuit, the impedance detection unit processes the continuously sampled values three times by using the sliding window mean algorithm, and the window width is dynamically adjusted according to the historical failure occurrence frequency. When the sampled value exceeds the tolerance range, the system calls the resistance-temperature correlation model in the historical database, and triggers the redundant heating mode after verifying the validity of the abnormal data. The tolerance range is set based on the thermal resistance characteristics of the aluminum thermal insulation bin material and the aging curve of the heating tape to prevent false triggering caused by accidental interference.

[0068] After the redundant heating mode is started, the self-check module extracts the temperature stability parameters from the historical database, including the standard deviation of the temperature rise rate in the main heating area and the pulse frequency fluctuation coefficient in the auxiliary heating area. The deformation compensation algorithm dynamically calculates the power distribution weight according to the deformation data of the composite insulation board of the current aluminum thermal insulation bin, combined with the temperature stability parameters. For example, when it is detected that the cold shrinkage deformation of the composite insulation board increases, the algorithm automatically increases the power ratio of the main heating area to compensate for the loss of heat conduction efficiency, and at the same time limits the maximum pulse frequency of the auxiliary heating area to avoid the deformation accumulation of the seal due to local overheating.

[0069] The reallocated power ratio and the data of the brake fluid circulation flow rate of the front vehicle are fused through the thermodynamic coupling model. The model is based on the correlation between the flow rate data of the brake fluid of the front vehicle and the heat loss coefficient of the rear vehicle, and weights and corrects the power distribution weights of the main and auxiliary heating areas. The fused data generates a heat distribution instruction set including area coding and time stamp, and the instruction set is encapsulated through the in-vehicle bus protocol and transmitted to the partition cooperation module. During the bus transmission process, a priority scheduling mechanism is adopted to send high-priority instructions to the heating tape drive unit in real time, and low-priority instructions are temporarily stored in the buffer queue and executed in batches according to the temperature control requirements. The execution result data is synchronously written into the historical database to provide constraint condition parameters for the genetic algorithm optimization, forming a closed-loop control link from abnormal detection to parameter iteration.

[0070] The above steps realize a technical closed-loop through hierarchical processing of anomaly verification, weight optimization and instruction scheduling: resistance anomaly triggers mode switching, historical data guides power distribution, and data fusion generates control instructions. Each link relies on the data center of the dynamic temperature control model to achieve cross-module cooperation, solves the problems of lagging redundant control response and energy efficiency imbalance in the existing solutions, and improves the temperature field regulation accuracy and system reliability of the split brake system under complex working conditions.

[0071] The explanations of the technical features in the technical solution of the present invention are as follows: Split heating module: A heat exchange unit linked to the cockpit thermal environment is set in the front vehicle braking assembly to improve the efficiency of the front vehicle braking system using the waste heat of the cockpit; an aluminum thermal insulation bin is built in the rear vehicle braking system, which integrates multi-zone heating tapes, distributed temperature control probes and mechanical clearance sensors. Through physical isolation and flexible heat conduction layer design, it adapts to the dynamic separation structure of the split vehicle body, solving the problem of different heat conduction paths between the front and rear vehicles.

[0072] Data fusion control module: Receives the temperature of the hydraulic unit, the deformation data of the seal and the historical braking pressure parameters of the vehicle bus from the distributed temperature control probes, and integrates multi-source sensing data to build a dynamic temperature control model. This model is optimized based on fuzzy control rules and genetic algorithms, generates zoned heating power commands, and realizes the dynamic matching of the heating strategy and the real-time working conditions. For example, it adjusts the pulse frequency weight according to the change in mechanical clearance to suppress the imbalance of the temperature field distribution.

[0073] Zoned cooperation module: Divides the aluminum thermal insulation bin into a main heating zone and an auxiliary heating zone. The main heating zone implements a continuous heating strategy to maintain the temperature of the brake fluid circulation pipeline, and the auxiliary heating zone dynamically adjusts the pulse heating frequency according to the real-time feedback data of the mechanical clearance sensor. By differentiating the control of the heating timing and power, it improves the multi-zone cooperative heating efficiency.

[0074] Self-check module: Periodically collects the impedance of the heating tape circuit and the calibration deviation data of the temperature control probe. When abnormal resistance or calibration deviation exceeds the limit is detected, it generates abnormal data including the fault area identification and triggers the redundant heating mode. For example, after the impedance detection unit identifies three consecutive sampling anomalies through the sliding window algorithm, it activates the standby heating tape circuit to avoid system failure caused by single-point failures.

[0075] Genetic algorithm optimization unit: Based on the initial temperature field data set and deformation sensor data, globally optimizes the control parameters through a multi-objective fitness function (such as temperature uniformity, energy consumption efficiency), generates an initial set of control parameters including proportional coefficients, integral times and fuzzy rule weights, provides an optimization starting point for the dynamic temperature control model, and reduces the risk of local optimality in manual parameter tuning.

[0076] Dynamic temperature control model: Through the real-time mechanical clearance change amount, the estimated value of brake fluid viscosity and the historical temperature rise curve data, it calls the clearance compensation algorithm and fuzzy control rules to calibrate the initial control parameters online. For example, it dynamically corrects the target temperature setting value of the main heating zone according to the deformation amount of the composite thermal insulation board, and synchronously adjusts the pulse duty cycle in combination with the viscosity change rate to achieve the real-time balance of heating power and heat loss.

[0077] Redundant heating mode: When abnormalities in the tracing heating circuit or temperature control probe are detected, the heat distribution coefficient is reconstructed based on the front vehicle's brake fluid circulation flow data. The optimal flow rate is calculated through a thermodynamic coupling model, and the heat loss compensation coefficient is corrected in combination with the deformation sensor data to generate a zoned heating instruction applicable to the fault scenario, ensuring temperature stability under abnormal conditions.

[0078] Gradient power reduction mechanism: Predict the thermal inertia delay time based on the historical temperature rise curve. After the temperature reaches the preset safety range, the main heating zone maintenance power is dynamically reduced according to the slope decreasing rule to avoid temperature overshoot caused by thermal inertia. At the same time, the power reduction instruction and the auxiliary heating zone pulse adjustment instruction are sent synchronously to optimize the overall energy consumption efficiency.

[0079] Deformation compensation algorithm: Based on the cold shrinkage deformation data of the aluminum thermal insulation bin composite thermal insulation board, call the gap compensation logic in the dynamic temperature control model to correct the target temperature setting value of the main heating zone. For example, when the deformation increases by 1 mm, the target temperature is increased by 2 °C to compensate for the loss of heat conduction efficiency caused by structural deformation.

[0080] The above technical features cooperate with each other through a closed-loop control architecture of multi-source data fusion, model optimization, and execution feedback to solve the problems of heating lag, local overheating, and energy consumption redundancy of the split body in low temperature, and improve the response speed and reliability of the braking system.

[0081] Dynamic temperature control model: A real-time control model constructed based on multi-source sensing data (hydraulic unit temperature, seal deformation, mechanical clearance change amount, and ambient temperature). This model processes non-linear temperature changes through fuzzy control rules. For example, the brake fluid viscosity change rate is mapped to the heating power adjustment gradient, and at the same time, the gap compensation algorithm is called to correct the heat conduction efficiency deviation caused by the deformation of the aluminum thermal insulation bin. The model outputs include the continuous power instruction of the main heating zone and the pulse frequency weight of the auxiliary heating zone, achieving a dynamic balance of temperature field distribution and energy consumption.

[0082] Genetic algorithm optimization unit: A global optimization model used to generate the initial control parameter set. Its input is the initial temperature field data set collected by the distributed temperature control probe and the deformation sensor data. The temperature control efficiency of different parameter combinations (such as temperature uniformity, energy consumption index) is evaluated through the fitness function, and parameters such as the proportional coefficient and integral time are output. The optimized parameter set is used as the input of the dynamic temperature control model to solve the local optimum problem caused by manual parameter adjustment and provide a benchmark for subsequent model fine-tuning.

[0083] Fuzzy control rule base: A logical decision-making module embedded in the dynamic temperature control model for handling uncertain and non-linear inputs. For example, when the feedback data from the mechanical clearance sensor exceeds the threshold, the fuzzy controller converts the clearance increment into a pulse frequency weight increment instruction according to the preset "clearance and pulse frequency" mapping table, and at the same time combines the historical temperature rise curve data to limit the adjustment range to prevent system oscillation caused by sudden changes in control instructions.

[0084] Deformation compensation algorithm: A sub-module of the dynamic temperature control model that specifically processes the low-temperature deformation data of the composite insulation board of the aluminum thermal insulation bin. The algorithm dynamically corrects the target temperature setting value of the main heating area according to the correlation between the deformation amount and the heat conduction path. For example, when it is detected that the clearance expands due to the cold shrinkage of the composite insulation board, the algorithm increases the target temperature according to the preset compensation coefficient to offset the increased heat loss due to structural deformation.

[0085] Delay compensation unit: A timing control model that predicts the influence of thermal inertia based on the historical temperature rise curve. This unit calculates the thermal inertia delay time according to the slope of the temperature rise curve and dynamically adjusts the triggering time of the gradient power reduction mechanism. For example, after the temperature in the main heating area reaches the safe range, the delay compensation unit generates a maintenance power instruction according to the power reduction slope fitted by historical data to avoid temperature overshoot caused by thermal inertia lag.

[0086] Heat distribution model: An emergency control model enabled in the redundant heating mode for reconstructing the thermal management strategy in the fault scenario. The model calculates the optimal heat transfer flow rate based on the front vehicle brake fluid circulation flow data, combines the feedback from the aluminum thermal insulation bin deformation sensor, dynamically corrects the heat loss compensation coefficient, and generates zoned heating instructions. For example, when the heating tape circuit is abnormal, the model preferentially increases the power ratio of the main heating area, and at the same time limits the maximum pulse frequency of the auxiliary heating area to maintain the temperature stability of the key area.

[0087] The above models cooperate through the data bus and the instruction queue: The genetic algorithm provides the initial parameters for global optimization, the dynamic temperature control model performs real-time fine-tuning, the fuzzy control and deformation compensation process non-linear inputs, and the delay compensation and heat distribution models handle timing and fault scenarios. The data interaction and instruction coordination of each model constitute a closed-loop control link, ultimately solving the problems of insufficient heating coordination and energy consumption redundancy of the split vehicle braking system at low temperatures.

[0088] In the specific implementation manner of the present invention, aiming at the low-temperature environment of the split vehicle braking system, precise thermal management is achieved through multi-source sensing data fusion and a closed-loop control architecture. In the front vehicle braking component, a thermocouple temperature sensor is integrated into the air outlet of the cockpit air conditioner to collect the temperature data of the cockpit thermal environment in real time and transmit it to the rear vehicle control module through the in-vehicle bus; in the rear vehicle aluminum thermal insulation bin, platinum resistance temperature sensors and strain gauge type deformation sensors are arranged in layers along the hydraulic unit pipeline, the sealing part installation position and the surface of the brake disc to collect the surface temperature of the hydraulic unit and the deformation displacement of the sealing part at a sampling frequency of 2 times per second. Combining with the mechanical clearance sensor to detect the cold shrinkage deformation of the composite thermal insulation board, an initial temperature field data set including the spatial temperature distribution matrix, the deformation displacement vector and the clearance change value is generated. The data fusion control module calls the genetic algorithm to perform global optimization on the initial data set. The fitness function comprehensively considers the temperature uniformity, energy consumption efficiency and response speed indicators, and iteratively generates an initial control parameter set of the proportional coefficient, integral time and fuzzy rule weight through genetic operations with a crossover probability of 0.8 and a mutation probability of 0.01, and transmits it to the parameter calibration interface of the dynamic temperature control model through the CAN bus protocol. The dynamic temperature control model calculates the viscosity value of the brake fluid based on the real-time mechanical clearance change amount and the temperature-viscosity relationship curve, calls the clearance compensation algorithm to dynamically correct the target temperature setting value of the main heating area, with the target temperature increasing by 1.2 °C for every 0.5 mm increase in the deformation amount. At the same time, the viscosity change rate is mapped to the power adjustment gradient through the fuzzy controller, and the continuous power slope of the main heating area and the pulse duty cycle of the auxiliary heating area are synchronously adjusted according to the preset rules of "low viscosity - high power" and "high viscosity - slow release heating". The partition cooperation module issues the calibrated pulse frequency weight to the auxiliary heating zone heating tape circuit within an adjustable range of 0.5 Hz - 5 Hz. The main heating area starts the gradient power reduction mechanism based on the historical temperature rise curve data. When the average temperature rise rate is lower than 75% of the historical peak value, the maintenance power is gradually reduced at a slope of 0.15 °C / min. The self-check module detects the impedance data of the heating tape circuit through the sliding window algorithm. When the continuous three sampling values exceed the ±10% tolerance range of the thermal resistance coefficient of the aluminum thermal insulation bin material, the redundant control unit is triggered to activate the standby heating tape circuit, and the heat loss compensation coefficient is reconstructed based on the turbine flow rate data of the front vehicle brake fluid circulation flow sensor. The optimal heat transfer flow rate is calculated by the thermodynamic coupling model and limited within 2.5 L / min, and a partition instruction with the power ratio of the main heating area increased to 65% is generated. The reconstructed parameters are written into the genetic algorithm constraint table to limit the search boundary of the next generation of control parameter sets, forming a closed-loop control link from data acquisition, model optimization to abnormal recovery, and solving the temperature field imbalance problem caused by low-temperature deformation and heat conduction differences of the split vehicle body.

[0089] The present invention solves the problem of thermal management coordination of split vehicle braking systems in low-temperature environments by constructing a closed-loop control mechanism for multi-source sensing data fusion. The split heating module deploys heat exchange units and aluminum thermal insulation bins in the front and rear vehicle braking systems respectively, integrates multi-region heating tapes and distributed temperature control probes, and collects data on the temperature of the hydraulic unit, the deformation of the seals, and the mechanical clearance in real time. The data fusion control module constructs a dynamic temperature control model based on the above multi-source data, globally optimizes the initial control parameters using a genetic algorithm, and generates zonal heating power commands. The zonal coordination module divides the aluminum thermal insulation bin into main and auxiliary heating zones according to the commands. The main heating zone executes a continuous heating strategy, and the auxiliary heating zone dynamically adjusts the pulse frequency based on the mechanical clearance feedback to achieve coordinated control of the heating zones and uniform distribution of the temperature field.

[0090] The dynamic temperature control model optimizes the problem of energy consumption redundancy through fuzzy control rules and a delay compensation mechanism. The model fine-tuning unit calls the clearance compensation algorithm to correct the target temperature of the main heating zone according to the real-time change rate of the brake fluid viscosity and the deformation of the composite thermal insulation board, and synchronously adjusts the pulse duty cycle of the auxiliary heating zone. The delay compensation unit predicts the thermal inertia delay time based on the historical temperature rise curve, dynamically adjusts the triggering timing of the gradient power reduction mechanism, and forms a real-time matching of heating power and energy consumption in combination with the CAN bus instruction issuance and execution log feedback. During the iterative optimization process of the genetic algorithm, the abnormal data collected by the self-check module and the reconstructed parameters of the historical mean are used as constraint conditions to limit the search space of the next-generation control parameter set, reduce ineffective energy consumption, and improve the control accuracy.

[0091] The redundant heating mode and the self-check module cooperate to ensure the reliability of the system. When an abnormal impedance in the heating tape circuit or a deviation exceeding the limit of the temperature control probe is detected, the self-check module triggers the activation instruction for the standby heating tape circuit, and reconstructs the heat distribution coefficient of the dynamic temperature control model based on the front vehicle brake fluid circulation flow data. The reconstructed compensation coefficient is input into the model fine-tuning process to generate zonal heating instructions suitable for the fault scenario, which are sent to the zonal coordination module through the vehicle bus. The historical database records the execution data and feeds it back to the genetic algorithm to optimize the robustness boundary conditions of the parameter set, forming a closed-loop control link from fault response to parameter iteration, and improving the anti-interference ability and operating stability of the braking system at low temperatures.

[0092] In view of the thermal management requirements of split vehicle braking systems in low-temperature environments, the present invention provides a heating device and control method for vehicle braking systems. Taking a certain articulated low-temperature operation vehicle as an example, it adopts a front-rear split vehicle body structure, and the rear vehicle has no independent air-conditioning system. The braking device needs to be equipped with a heating device separately. The following is an embodiment of the aluminum thermal insulation bin of the rear vehicle braking system of this vehicle. Please refer to Figure 2 , and the embodiment content is as follows.

[0093] The rear vehicle braking system is equipped with an aluminum thermal insulation bin as the basic structure. Inside the bin, a multi-zone heating tape, distributed temperature control probes, and mechanical clearance sensors are integrated. Among them, a composite thermal insulation board is laid on the inner wall of the aluminum thermal insulation bin. The thickness of the thermal insulation material is 10 mm, and the thermal conductivity is less than 0.021 W / m.K. The low thermal conductivity characteristic is used to reduce the heat exchange loss inside and outside the bin. The heating tape uses a working voltage of DC-24V, adapts to the vehicle-mounted power system, and provides heat sources for key components of the braking system (such as hydraulic units, seals, and brake fluid pipelines).

[0094] The split-type heating module sets a heat exchange unit linked to the cockpit thermal environment in the front vehicle braking assembly to utilize the waste heat of the cockpit to assist the front vehicle braking system in warming up; in the rear vehicle aluminum thermal insulation bin, the multi-zone heating tape is arranged in zones according to the heat requirements of different components of the braking system. The distributed temperature control probes are laid in layers along the surface of the hydraulic unit, the installation position of the seal, and the circumferential direction of the brake disc to collect the temperature of the hydraulic unit, the deformation data of the seal, and the ambient temperature in real time; the mechanical clearance sensor is deployed at the splicing joint of the composite thermal insulation board to monitor the change in the mechanical clearance caused by low-temperature cold shrinkage. The above sensors generate initial thermal distribution parameters and transmit them to the data fusion control module.

[0095] After receiving multi-source data, the data fusion control module constructs a dynamic temperature control model based on the temperature of the hydraulic unit, the deformation of the seal, the ambient temperature, and the historical parameters of the vehicle-mounted bus braking pressure. This model combines the genetic algorithm to globally optimize the initial temperature field data set and generates an initial control parameter set including the proportional coefficient and the integral time; at the same time, the model fine-tuning unit dynamically calibrates the control parameters according to the real-time change of the mechanical clearance sensor and the brake fluid viscosity value calculated from the temperature-viscosity relationship curve: when the clearance expands due to the cold shrinkage of the composite thermal insulation board, the gap compensation algorithm is called to correct the target temperature setting value of the main heating zone (for example, when the deformation amount increases by 0.5 mm each time, the target temperature is increased by 1.2 °C); according to the change rate of the brake fluid viscosity, the continuous heating power slope of the main heating zone and the pulse heating duty ratio of the auxiliary heating zone are synchronously adjusted through fuzzy control rules (for example, when the viscosity drops rapidly, the power rising rate of the main heating zone is reduced to avoid local overheating).

[0096] The zoning coordination module divides the aluminum thermal insulation bin into a main heating zone (covering the hydraulic unit and the brake fluid pipeline) and an auxiliary heating zone (covering the seal and the mechanical clearance sensitive parts). The main heating zone controls the power output of the heating tape based on the continuous heating strategy. When the temperature of the hydraulic unit is lower than the critical threshold, high-power rapid heating is started. After the temperature reaches the safe range, the delay compensation unit calls the historical temperature rise curve data to predict the thermal inertia delay time and generates a maintenance power command by superimposing the gradient power reduction coefficient; the auxiliary heating zone dynamically adjusts the pulse heating frequency according to the feedback of the mechanical clearance sensor (for example, when the gap increment exceeds the threshold, the pulse frequency is increased to compensate for the heat loss).

[0097] The self-check module periodically collects data on the impedance of the tracing cable circuit and the calibration deviation of the temperature control probe: The impedance detection unit monitors the resistance change rate using a sliding window algorithm and triggers the redundant heating mode when the sampled values exceed the tolerance range (±10%) for three consecutive times, activating the standby tracing cable circuit; the deviation calibration unit reconstructs the compensation coefficient of the temperature control probe based on the historical mean and writes it into the dynamic temperature control model calibration parameter table; when the accuracy of the mechanical clearance sensor exceeds the limit, the redundant control unit switches to the heat distribution model driven by the data of the front vehicle's brake fluid circulation flow rate, calculates the optimal flow rate for transferring heat to the rear vehicle (for example, limited within 2.5 L / min), reconstructs the heat loss compensation coefficient in combination with the deformation data of the aluminum thermal insulation bin, and generates a zoned heating instruction under fault scenarios.

[0098] Through the above structure and control method, the rear vehicle braking system can achieve multi-region collaborative temperature control in low-temperature environments: Distributed sensors continuously feedback the thermal state, and the dynamic temperature control model combines genetic algorithm optimization and online calibration to accurately adjust the power distribution between the main and auxiliary heating zones; the self-check module and the redundant mode ensure temperature stability under abnormal conditions; the aluminum thermal insulation bin and low-thermal-conductivity thermal insulation materials reduce heat loss, and the DC-24V tracing cable is adapted to the vehicle power supply, effectively solving the problems of temperature field imbalance, heating lag, and energy consumption redundancy caused by low temperature in the split-body vehicle braking system, and improving the braking response speed and system reliability.

Claims

1. A heating device for a vehicle braking system, characterized in that, Comprising: A split heating module configured to set a first heat exchange unit linked to the cockpit thermal environment in the front vehicle braking assembly, and construct an aluminum thermal insulation bin in the rear vehicle braking system. A multi-zone heating tape, distributed temperature control probes, and a mechanical clearance sensor are integrated in the aluminum thermal insulation bin to generate initial thermal distribution parameters and transmit them to the data fusion control module; A data fusion control module, connected to the split heating module, for receiving hydraulic unit temperature data, seal deformation data, and ambient temperature data from the distributed temperature control probes, and accessing the braking pressure history parameters of the vehicle-mounted bus. Based on the hydraulic unit temperature data, seal deformation data, and ambient temperature data, a dynamic temperature control model is constructed, and closed-loop control parameters including zoned heating power instructions are output to the zoned cooperation module; A zoned cooperation module, connected to the data fusion control module, divides the aluminum thermal insulation bin into a main heating zone and an auxiliary heating zone, receives the closed-loop control parameters and executes a continuous heating strategy and pulse heating frequency adjustment. The main heating zone controls the power output of the heating tape based on the continuous heating strategy, and the auxiliary heating zone adjusts the pulse heating frequency according to the real-time feedback data of the mechanical clearance sensor; A self-check module, connected to the zoned cooperation module, periodically collects the impedance of the heating tape circuit and the calibration deviation data of the temperature control probe. When abnormal impedance or calibration deviation exceeding the limit is detected, abnormal data including a fault area identifier is generated and transmitted to the data fusion control module; Among them, the data fusion control module iteratively optimizes the control parameters of the dynamic temperature control model according to the initial thermal distribution parameters and the abnormal data, and issues the updated closed-loop control parameters to the zoned cooperation module to form a closed-loop control link from data acquisition, model optimization to instruction execution.

2. The heating device for a vehicle braking system according to claim 1, characterized in that, The data fusion control module includes: A genetic algorithm optimization unit for generating an initial control parameter set based on the initial temperature field data set of the distributed temperature control probes and the deformation sensor data of the aluminum thermal insulation bin, and transmitting it to the model fine-tuning unit; A model fine-tuning unit, receiving the real-time change amount of the mechanical clearance sensor and the estimated value of the brake fluid viscosity, online calibrates the initial control parameter set based on the dynamic temperature control model, and outputs the calibrated pulse frequency weight to the pulse heating controller in the auxiliary heating zone; A delay compensation unit, calling the historical temperature rise curve data stored in the self-check module to predict the thermal inertia delay time, dynamically adjusts the trigger timing of the gradient power reduction mechanism, and issues the adjusted timing instruction to the heating tape drive circuit in the main heating zone through the CAN bus; Among them, the pulse frequency weight output by the model fine-tuning unit and the timing instruction of the delay compensation unit together constitute the closed-loop control parameters to drive the zoned cooperation module to execute the heating strategy.

3. The heating device for a vehicle braking system according to claim 2, characterized in that, The delay compensation unit performs the following operations: When the temperature of the hydraulic unit is lower than the critical threshold, send a high-power rapid heating instruction to the heating tape drive circuit in the main heating zone; After the temperature reaches the preset safe range, based on the thermal inertia parameters of the dynamic temperature control model, calculate the thermal inertia delay time according to the slope of the historical temperature rise curve, and generate a maintenance power instruction by superimposing the gradient power reduction coefficient; The maintenance power instruction is written into the instruction queue of the partition cooperation module synchronously with the pulse frequency adjustment instruction of the auxiliary heating zone as part of the closed-loop control parameters.

4. The heating device for a vehicle braking system according to claim 3, characterized in that, The model fine-tuning unit includes: The deformation compensation sub-module, based on the deformation amount of the composite insulation board of the aluminum insulation bin, calls the gap compensation algorithm of the dynamic temperature control model to correct the target temperature setting value of the main heating zone; The viscosity feedback sub-module calculates the brake fluid viscosity in real time according to the temperature-viscosity relationship curve, and dynamically adjusts the continuous heating power of the main heating zone and the pulse heating duty ratio of the auxiliary heating zone through fuzzy control rules; Among them, the gap compensation coefficient output by the deformation compensation sub-module and the viscosity adjustment parameter of the viscosity feedback sub-module are jointly input into the genetic algorithm optimization unit as the optimization boundary conditions of the next-generation control parameter set.

5. The heating device for a vehicle braking system according to claim 4, characterized in that, The self-check module includes: The impedance detection unit periodically collects the resistance change rate of the heating tape circuit. When abnormal resistance fluctuations are detected, it sends a standby circuit activation instruction to the partition cooperation module; The deviation calibration unit reconstructs the temperature compensation coefficient of the temperature control probe based on historical mean data and writes the reconstructed coefficient into the calibration parameter table of the dynamic temperature control model; The redundant control unit switches to the heat distribution model based on the front vehicle brake fluid circulation flow data when the accuracy of the mechanical clearance sensor is detected to be exceeded, and feeds back the reconstructed distribution coefficient to the genetic algorithm optimization unit.

6. A heating control method for a vehicle braking system, applied to the heating device for a vehicle braking system according to any one of claims 1 to 5, characterized in that, It includes: Obtain the front vehicle cockpit temperature data and the hydraulic unit temperature and seal deformation data collected by the distributed temperature control probes of the rear vehicle aluminum insulation bin, integrate the data into the initial temperature field data set and input it into the genetic algorithm optimization process; Globally optimize the initial temperature field data set based on the genetic algorithm, generate an initial control parameter set including the proportional coefficient and integral time and transmit it to the parameter calibration interface of the dynamic temperature control model; According to the real-time mechanical clearance change amount and the estimated brake fluid viscosity, online fine-tune the initial control parameter set through the dynamic temperature control model, and output the calibrated pulse frequency weight and continuous heating power instruction to the partition cooperation control queue; Send the pulse frequency weight to the heating tape circuit of the rear vehicle auxiliary heating zone, and at the same time call the historical temperature rise curve data stored in the self-check module, dynamically adjust the maintenance power of the main heating zone based on the gradient power reduction mechanism and update the power distribution parameters of the dynamic temperature control model; When abnormal impedance of the heating tape circuit or deviation of the temperature control probe exceeds the limit is detected, switch to the redundant heating mode and reconstruct the heat distribution coefficient of the dynamic temperature control model based on the front vehicle brake fluid circulation flow data, and feed back the reconstructed coefficient to the genetic algorithm optimization process as the constraint condition of the next-generation parameter set.

7. The heating control method for a vehicle braking system according to claim 6, wherein According to the real-time mechanical clearance change amount and the estimated brake fluid viscosity, online fine-tune the initial control parameter set through the dynamic temperature control model, and output the calibrated pulse frequency weight and continuous heating power instruction to the partition cooperation control queue includes: According to the deformation amount of the composite insulation board of the aluminum insulation bin, call the gap compensation algorithm of the dynamic temperature control model to dynamically correct the target temperature setting value of the main heating zone; Based on the temperature-viscosity relationship curve, calculate the viscosity change rate of the brake fluid in real time, and synchronously adjust the heating power of the main heating zone and the pulse duty cycle of the auxiliary heating zone through fuzzy control rules; Write the corrected target temperature set value and the pulse duty cycle parameter into the parameter constraint table of the genetic algorithm optimization unit for updating the next generation of control parameter sets.

8. The heating control method for a vehicle braking system according to claim 7, wherein Based on the temperature-viscosity relationship curve, calculating the viscosity change rate of the brake fluid in real time and synchronously adjusting the heating power of the main heating zone and the pulse duty cycle of the auxiliary heating zone includes: When the feedback data of the mechanical clearance sensor exceeds the threshold set by the self-check module, send a pulse frequency weight increment instruction to the delay compensation unit; According to the correlation between the viscosity change rate of the brake fluid and the historical temperature rise curve, dynamically adjust the continuous heating power slope of the main heating zone and generate a power reduction instruction; The adjusted parameters are synchronously sent to the heating tape drive unit through the CAN bus, and the execution log is recorded in the historical database for genetic algorithm iteration.

9. The heating control method for a vehicle braking system according to claim 8, characterized in that, When the impedance of the heating tape circuit is detected to be abnormal or the deviation of the temperature control probe exceeds the limit, switch to the redundant heating mode and reconstruct the heat distribution coefficient of the dynamic temperature control model based on the front vehicle brake fluid circulation flow data, and feedback the reconstructed coefficient to the genetic algorithm optimization process as a constraint condition for the next generation of parameter sets, including: after activating the standby heating tape circuit, calculate the optimal flow rate of heat transfer to the rear vehicle based on the front vehicle brake fluid circulation flow sensor data; According to the optimal flow rate and the deformation sensor data of the aluminum thermal insulation bin, reconstruct the heat loss compensation coefficient of the dynamic temperature control model; Input the reconstructed compensation coefficient into the model fine-tuning process, generate a zoned heating instruction applicable to the fault scenario and write it into the instruction queue.

10. The heating control method for a vehicle braking system according to claim 9, wherein, It also includes: Periodically collect the resistance change rate data of the heating tape circuit. When it is detected that the sampling values of three consecutive times exceed the tolerance range of the impedance detection unit, trigger the redundant heating mode; In the redundant heating mode, based on the temperature stability parameter of the historical mean data, call the deformation compensation algorithm to reallocate the power ratio between the main heating zone and the auxiliary heating zone; Fuse the reallocated power ratio with the front vehicle brake fluid circulation flow data, generate a new heat distribution instruction and transmit it to the zoned cooperation module through the vehicle bus.

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