Collaborative Optimization Of Aerodynamic Drag And Heat Dissipation Performance In Vehicle Engine Compartment

Most of the key parts of the vehicle are integrated in the engine cabin,and the aerodynamic performance and heat dissipation performance in the cabin directly determine whether these parts can operate normally,which has a great impact on the vehicle performance.The flow rate and flow characteristics of cabin cooling gas not only have a great influence on the internal flow drag,but also have a decisive influence on the heat dissipation of heating elements.In order to dissipate heat efficiently and increase cooling gas flow greatly,the internal flow resistance will increase,which is not conducive to fuel economy.However,in order to reduce the internal flow drag and reduce the cooling gas flow,it may lead to insufficient heat dissipation.The two are a pair of contradictory bodies,which need to be optimized cooperatively,so as to find an optimal balance point of cooling gas flow,and optimize the aerodynamic performance in the cabin when meeting the cooling requirements.In this paper,a real vehicle was taken as the research object.Based on computational fluid dynamics and Star-ccm+ software as the simulation tool,the design scheme based on Isight platform was proposed with low-resistance and high-efficiency heat dissipation in the cabin as the collaborative optimization goal.The main research contents are as follows:(1)CFD simulation was carried out for the original model under high-speed operating conditions.By obtaining the flow field and temperature field information of important sections in the cabin,the aerodynamic performance and heat dissipation performance in the cabin were analyzed and evaluated,and the design variables were determined and the optimization objectives were proposed;(2)Optimize aerodynamic drag in the cabin within the discipline of aerodynamics.In order to explore the response relationship between design vector and aerodynamic performance,experimental design was carried out.The approximate model was established through the experimental sample points,and the cross-validation error analysis was carried out on it.On the premise of satisfying the accuracy,the multi-island genetic algorithm was used to find the model with the least internal flow resistance coefficient,and data mining was carried out on the optimized results.(3)Within the discipline of heat transfer,the maximum surface temperature of fan cover is optimized.In order to explore the response relationship between design vector andheat dissipation performance,experimental design was carried out.The approximate model was established through the experimental sample points,and the cross-validation error analysis was carried out on it.Under the premise of satisfying the accuracy,the multi-island genetic algorithm was used to find the model with the minimum surface temperature,and the data mining was carried out on the optimized results.(4)Establish a collaborative optimization mathematical model of aerodynamic performance and heat dissipation performance,and build the basic framework and work flow of the optimization.Isight platform was used to carry out the coordinated optimization of low-drag and high-efficiency heat dissipation in the engine compartment,so as to find the optimal cooling air flow that could balance the cooperative relationship between the two.The results of collaborative optimization show that the internal flow drag coefficient is reduced by 11.08% compared with the original model,from 9.68% of the total vehicle drag coefficient of the original model to 8.65%,a decrease of 1.03%.To some extent,the aerodynamic performance of the engine cabin is improved and the fuel economy is improved.The maximum surface temperature of the fan cover was reduced by 9.39?,a decrease of 5.93% from the original model,which effectively avoided the occurrence of thermal damage,reduced the thermal damage to the windings of the cooling fan motor,and improved the cooling performance of the engine cabin.The simulation error analysis of the model after collaborative optimization showed that the error of aerodynamic drag coefficient was 0.12%,and the temperature error was 0.58%,both within 5%,indicating the high reliability of the optimization results.The purpose of this paper is to solve the contradiction between the flow drag and heat dissipation performance in the engine cabin by using the collaborative optimization algorithm,and to seek the optimal cooling air flow that can balance the two.It provides a research method for the design and optimization of engine cabin front-end structure.