A multi-objective optimization method for under-the-hood thermal management of vehicles. (25th June 2021)

• Record Type: Journal Article
• Authors: Zhang, Jie; Wang, Qidong; Shu, Chi-Min; Zhang, Min; Lin, Jianwei
• Is Part Of: Applied thermal engineering. Volume 192(2021)
• Publication Date: 2021-06-25
• Subjects: 1D/3D collaborative simulation analysis -- Optimization objectives -- Pareto front -- Environmental chamber experiments -- Thermal risk; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2021.116818
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: The multiobjective optimization problems of thermal management were critical. A 1D/3D coupling model for under-the-hood thermal management system was established. A prediction model between key influencing factors and optimisation objectives were established. A systematic multiobjective optimisation method for thermal management of vehicles was proposed. Environmental chamber experiment was conducted to verify the proposed method. Abstract: This study proposes a systematic multi-objective optimization method for thermal management of passenger vehicles. We address the problems of the battery surface temperature and the engine outlet water temperature exceeding the allowable values. First, the causes of excessive temperature were studied through 1D/3D collaborative simulation analysis, and the key influencing factors of the optimization objectives were determined: radiator core thickness ( l1 ), radiator band pitch ( λ1 ), the blocking percentage ( θ ) between the cooling module and mounting frame, and the grille opening ratio ( α ). Second, a training set of key influencing factors was created, and a prediction model between key influencing factors and optimization objectives was developed. Third, the prediction model was applied as a fitness evaluation model for particle swarm optimization (PSO), and the Pareto front of the optimization objectives was calculated. Finally, the optimal point of the Pareto front was selected for simulation and environmental chamber experiments to verify the proposed method. The experimental results indicated that when α = 27%, l 1 = 27.9 mm, λ 1 = 3.4 mm, and θ = 80%, the battery surface temperature and the engine outlet water temperature reduced promptly; the experimental results revealed that this method alleviated the battery surface temperature and the engine outlet water temperature promptly, and the decreasing amplitude was 9.6% and 5.9%, respectively, both met the experimental requirements. This method can effectively minimize the thermal risk of vehicles.