Multi-objective optimization thermal management system

Abstract

The invention relates to the technical field of heat management, in particular to a multi-objective optimization heat management system, and aims to solve the problems that traditional heat management systems often have limitations in design, mostly can only focus on a single heat dissipation or preheating function, and the capability of comprehensively processing various heat management requirements is lacked. Comprising a temperature sensor array, a heat management execution module, an intelligent control module and a data interaction module, temperature data of key areas in a vehicle are collected in real time, and the system can accurately adjust the temperature environment in the vehicle by combining the real-time working condition of the vehicle, so that the vehicle temperature is controlled. According to the method, the engine, the battery and other key components are always in the most suitable working temperature range, the multi-objective optimization algorithm not only pays attention to the accuracy of temperature adjustment, but also gives consideration to the maximization of the energy utilization efficiency, and the system can reduce the energy consumption as much as possible and reduce the energy consumption of the thermal management system while meeting the temperature adjustment requirement.

Description

Technical Field

[0001] The present invention relates to the field of thermal management technology, and more particularly to a multi-objective optimization thermal management system. Background Art

[0002] With the rapid development of new energy vehicle technology, the continuous improvement of vehicle performance and cruising range, the requirements for thermal management systems have also reached an unprecedented level. Key components such as battery packs, motors, and power electronic control units in new energy vehicles will generate a lot of heat during operation. If not effectively managed, it will directly affect the safety, reliability and overall performance of the vehicle.

[0003] Under complex and changeable driving conditions, such as high-speed driving, sudden acceleration, climbing and extreme weather conditions, the performance of traditional thermal management systems is often unsatisfactory. They are unable to respond and adapt to these changes quickly, resulting in inefficient thermal management and may even cause overheating risks, affecting battery life and vehicle performance.

[0004] More importantly, traditional thermal management systems generally lack intelligence and adaptive capabilities. They cannot perceive the vehicle's operating status and external environmental changes in real time, and cannot automatically adjust the control strategy according to these changes to achieve the optimal thermal management effect. This static, fixed control mode not only limits the performance of the thermal management system, but also causes unnecessary energy waste, reducing the economy and environmental protection of new energy vehicles.

[0005] In view of this, we propose a multi-objective optimization thermal management system. Summary of the invention

[0006] The purpose of the present invention is to provide a multi-objective optimization thermal management system, aiming to solve the problem that traditional thermal management systems often have limitations in design, most of which can only focus on a single heat dissipation or preheating function and lack the ability to comprehensively handle multiple thermal management requirements.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a multi-objective optimization thermal management system, including a temperature sensor array, a thermal management execution module, an intelligent control module and a data interaction module:

[0008] The temperature sensor array is distributed inside the vehicle to collect temperature data in real time;

[0009] The thermal management execution module is used to execute vehicle temperature adjustment;

[0010] The intelligent control module calculates the optimal control strategy based on the operating conditions and temperature data;

[0011] The data interaction module is used for the vehicle to communicate and exchange data with an external system.

[0012] Preferably, the thermal management execution module includes a cooling fan, a heating element, and a liquid cooling system, which are used to perform temperature adjustment operations according to instructions issued by the intelligent control module to ensure that various components inside the vehicle are within a suitable operating temperature range.

[0013] Preferably, the intelligent control module includes a processor, a memory and a pre-installed multi-objective optimization algorithm, which can receive data from the temperature sensor array, combine the vehicle's implementation speed, acceleration, slope, and ambient temperature, calculate the optimal control strategy through the multi-objective optimization algorithm, and send it to the thermal management execution module for execution.

[0014] Preferably, the objective function of the multi-objective optimization algorithm is in the form of:

[0015]

[0016] Where x is the control variable vector, ω i is the weight of the i-th target, satisfying And ω i ≥0.

[0017] Preferably, a set of constraints is also included:

[0018] C={c i (x)≤0,c2(x)≤0,...,c m (x)≤0}

[0019] where c i (x) is the i-th constraint, and m is the number of constraints, which ensures the feasibility and safety of the control strategy in practical applications.

[0020] Preferably, the objective function of the multi-objective optimization algorithm includes at least minimizing temperature deviation (f1(x)), maximizing energy utilization efficiency (f2(x)), minimizing thermal management system energy consumption (f3(x)) and extending the life of key components (f4(x)), and is optimized using methods such as the weighted sum method or the ε-constraint method.

[0021] Preferably, the intelligent control module dynamically adjusts the weight distribution in the multi-objective optimization algorithm according to historical operating data and user preferences to further optimize the control strategy.

[0022] Preferably, the data interaction module supports wireless communication technology, and can obtain external environmental information in real time, such as weather forecasts and road conditions, and adjust the control strategy accordingly.

[0023] Preferably, it also includes a fault detection and early warning module for real-time monitoring of the operating status of the temperature sensor array, the thermal management execution module, the intelligent control module and the data interaction module.

[0024] A control method for a multi-objective optimization thermal management system based on any of the above, the method comprising the following steps:

[0025] S1, collect temperature data and implement working condition data;

[0026] S2, analyzing external environment information and vehicle operation status;

[0027] S3, calculate the optimal control strategy using a multi-objective optimization algorithm;

[0028] S4, execute control strategy and monitor the effect; adjust control strategy based on feedback.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. The present invention can accurately adjust the temperature environment inside the vehicle by collecting temperature data of key areas inside the vehicle in real time and combining it with the real-time working conditions of the vehicle to ensure that key components such as the engine and battery are always in the most suitable operating temperature range. The multi-objective optimization algorithm not only focuses on the accuracy of temperature regulation, but also takes into account the maximization of energy utilization efficiency. The system can reduce energy consumption as much as possible while meeting the temperature regulation requirements, reduce the energy consumption of the thermal management system, help improve the fuel economy of the vehicle or extend the cruising range of the electric vehicle, thereby improving the overall performance and stability of the vehicle.

[0031] 2. The present invention can dynamically adjust the weight distribution in the multi-objective optimization algorithm according to historical operating data and user preferences, so as to further optimize the control strategy. In addition, the data interaction module also supports wireless communication technology, and can obtain external environmental information (such as weather forecast, road conditions, etc.) in real time, providing the system with more comprehensive and accurate input data. These functions not only enhance the intelligence of the system, but also enable the system to use energy more efficiently, reduce the energy consumption of the thermal management system, and extend the service life of key components. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 Block diagram of the thermal management system for multi-objective optimization. DETAILED DESCRIPTION

[0033] like Figure 1 As shown, the present invention relates to a multi-objective optimization thermal management system, including a temperature sensor array, a thermal management execution module, an intelligent control module and a data interaction module:

[0034] The temperature sensor array is distributed inside the vehicle to collect temperature data in real time;

[0035] The thermal management execution module is used to execute vehicle temperature adjustment;

[0036] The intelligent control module calculates the optimal control strategy based on the operating conditions and temperature data;

[0037] The data interaction module is used for the vehicle to communicate and exchange data with an external system;

[0038] The thermal management execution module includes a cooling fan, a heating element, and a liquid cooling system, and is used to perform temperature adjustment operations according to the instructions issued by the intelligent control module to ensure that the internal components of the vehicle are within a suitable operating temperature range;

[0039] The intelligent control module includes a processor, a memory and a pre-installed multi-objective optimization algorithm, which can receive data from the temperature sensor array, combine the vehicle's implementation speed, acceleration, slope, and ambient temperature, calculate the optimal control strategy through the multi-objective optimization algorithm, and send it to the thermal management execution module for execution;

[0040] The specific form of the objective function of the multi-objective optimization algorithm is:

[0041]

[0042] Where x is the control variable vector, ω i is the weight of the i-th target, satisfying And ω i ≥0;

[0043] Also includes a set of constraints:

[0044] C={c i (x)≤0,c2(x)≤0,...,c m (x)≤0}

[0045] where c i (x) is the i-th constraint, and m is the number of constraints, which ensures the feasibility and safety of the control strategy in practical applications;

[0046] The objective function of the multi-objective optimization algorithm at least includes minimizing temperature deviation (f1(x)), maximizing energy utilization efficiency (f2(x)), minimizing energy consumption of thermal management system (f3(x)) and extending the life of key components (f4(x)), and is optimized by using weighted sum method or ε-constraint method;

[0047] The intelligent control module dynamically adjusts the weight distribution in the multi-objective optimization algorithm according to historical operation data and user preferences to further optimize the control strategy;

[0048] The data interaction module supports wireless communication technology and can obtain external environmental information in real time, such as weather forecast and road condition information, and adjust the control strategy accordingly;

[0049] It also includes a fault detection and early warning module for real-time monitoring of the operating status of the temperature sensor array, the thermal management execution module, the intelligent control module, and the data mutual module;

[0050] Specifically, arrays of temperature sensors are arranged at key locations inside the vehicle. These sensors can collect temperature data of each area in real time and accurately, providing a reliable basis for subsequent temperature adjustment.

[0051] Through the thermal management execution module, which includes a cooling fan, a heating element and a liquid cooling system, when the intelligent control module issues an instruction, the thermal management execution module can respond quickly and accurately control the temperature inside the vehicle by adjusting the speed of the cooling fan, the power of the heating element or the flow of the liquid cooling system to ensure that each component is within an appropriate operating temperature range.

[0052] The intelligent control module is the core of the entire system. It has a built-in high-performance processor and memory, as well as a built-in multi-objective optimization algorithm. The algorithm can receive data collected by the temperature sensor array, and at the same time combine the vehicle's real-time driving status (such as speed, acceleration, slope) and external ambient temperature to perform complex calculations and analysis. Through the optimization algorithm, the intelligent control module can derive the optimal control strategy and send the strategy to the thermal management execution module for execution.

[0053] In the multi-objective optimization algorithm, a specific objective function is set. This function takes into account multiple factors, including minimizing temperature deviation, maximizing energy utilization efficiency, minimizing energy consumption of the thermal management system, and extending the life of key components. In order to balance these goals, weight coefficients are introduced to ensure that the sum of all weights is 1 and each weight is non-negative. In this way, the algorithm can find the best compromise while meeting various goals.

[0054] In addition, constraints are set to ensure that the control strategy is both feasible and safe in practical applications.

[0055] In the intelligent control module, the function of dynamically adjusting weight distribution according to historical operation data and user preferences is realized. In this way, the system can automatically optimize the control strategy according to the vehicle usage and the actual needs of the user, and provide more personalized services.

[0056] The data interaction module is the bridge between the system and the outside world. It supports wireless communication technology and can obtain external environmental information in real time, such as weather forecasts, road conditions, etc. These can help the system predict future temperature changes more accurately and adjust control strategies accordingly.

[0057] Finally, a fault detection and early warning module is added to the system. This module can monitor the operating status of the temperature sensor array, thermal management execution module, intelligent control module and data interaction module in real time. Once an abnormal situation is found, it will immediately issue an early warning signal to remind the user to check and repair to ensure the stable operation of the system.

[0058] The embodiments of the present invention disclose preferred embodiments, but are not limited thereto. A person skilled in the art can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. However, as long as they do not deviate from the spirit of the present invention, they are all within the protection scope of the present invention.

Claims

1. A multi-objective optimization thermal management system, characterized in that: Including temperature sensor array, thermal management execution module, intelligent control module and data interaction module: The temperature sensor array is distributed inside the vehicle to collect temperature data in real time; The thermal management execution module is used to execute vehicle temperature adjustment; The intelligent control module calculates the optimal control strategy based on the operating conditions and temperature data; The data interaction module is used for the vehicle to communicate and exchange data with an external system.

2. A multi-objective optimization thermal management system according to claim 1, characterized in that: The thermal management execution module includes a cooling fan, a heating element, and a liquid cooling system, and is used to perform temperature adjustment operations according to instructions issued by the intelligent control module to ensure that various components inside the vehicle are within a suitable operating temperature range.

3. The multi-objective optimization thermal management system according to claim 1, characterized in that: The intelligent control module includes a processor, a memory and a pre-installed multi-objective optimization algorithm. It can receive data from the temperature sensor array, combine the vehicle's implementation speed, acceleration, slope, and ambient temperature, calculate the optimal control strategy through the multi-objective optimization algorithm, and send it to the thermal management execution module for execution.

4. A multi-objective optimization thermal management system according to claim 3, characterized in that: The specific form of the objective function of the multi-objective optimization algorithm is: Where x is the control variable vector, ω i is the weight of the i-th target, satisfying And ω i ≥0.

5. A multi-objective optimization thermal management system according to claim 4, characterized in that: Also includes a set of constraints: C={c i (x)≤0,c2(x)≤0,...,c m (x)≤0} where c i (x) is the i-th constraint, and m is the number of constraints, which ensures the feasibility and safety of the control strategy in practical applications.

6. A multi-objective optimization thermal management system according to claim 5, characterized in that: The objective functions of the multi-objective optimization algorithm include at least minimizing temperature deviation (f1(x)), maximizing energy utilization efficiency (f2(x)), minimizing energy consumption of the thermal management system (f3(x)), and extending the life of key components (f4(x)), and are optimized using methods such as the weighted sum method or the ε-constraint method.

7. The multi-objective optimization thermal management system according to claim 1, characterized in that: The intelligent control module dynamically adjusts the weight distribution in the multi-objective optimization algorithm according to historical operation data and user preferences to further optimize the control strategy.

8. The multi-objective optimization thermal management system according to claim 1, characterized in that: The data interaction module supports wireless communication technology and can obtain external environmental information in real time, such as weather forecast and road condition information, and adjust the control strategy accordingly.

9. The multi-objective optimization thermal management system according to claim 1, characterized in that: It also includes a fault detection and early warning module for real-time monitoring of the operating status of the temperature sensor array, thermal management execution module, intelligent control module and data interaction module.

10. A control method for a multi-objective optimization thermal management system based on any one of claims 1 to 9, characterized in that: The method comprises the following steps: S1, collect temperature data and implement working condition data; S2, analyzing external environment information and vehicle operation status; S3, calculate the optimal control strategy using a multi-objective optimization algorithm; S4, execute control strategy and monitor the effect; adjust control strategy based on feedback.

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