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<p>This study presents an in-depth investigation into the optimization of a hybrid automobile battery cooling system that integrates Peltier blocks with a conventional radiator. An experimental design strategy was chosen according to the variance of the orthogonal L16 sequences utilizing Taguchi’s method and Grey Relational Analysis (GRA). The analysis systematically evaluates the impact of the flow rate, coolant ratio, and fan speed on key performance metrics, including the hybrid temperature difference, bulk mean temperature, heat energy, Reynolds number, convective heat transfer coefficient, and overall heat transfer coefficient. The findings suggested that the flow rate and coolant ratio are critical factors influencing the system efficiency, while the integration of time bound Peltier heat sink reduces the impact of fan speed to stationary level. The GRA analysis identified the optimal operating conditions of an LPH flow rate of 19, coolant ratio of 70%, and fan speed of 3&#xa0;m/s, striking a balance between maximized heat transfer and favourable temperature difference. The Taguchi interaction plots and Machine learning visualization tool Heat Map are generated to show the correlation between variable. Significant improvements in cooling performance and energy efficiency were achieved at optimal interaction of flow rate and coolant ratio. This research provides valuable insights for engineers in designing and configuring efficient thermal management systems for future hybrid vehicles, showcasing the potential of Peltier-based cooling systems in advancing automotive technology.</p>

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Optimization of Process Parameters of Novel Hybrid Automotive Battery Cooling System using GRA -Taguchi and Heatmap Visualization

  • 期刊论文

  • 发表日期：

    2025年7月11日

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  • Himanshu Sharma,
  • Gaurav Saxena,
  • R. S. Rajput,
  • Ravindra Randa

摘要

This study presents an in-depth investigation into the optimization of a hybrid automobile battery cooling system that integrates Peltier blocks with a conventional radiator. An experimental design strategy was chosen according to the variance of the orthogonal L16 sequences utilizing Taguchi’s method and Grey Relational Analysis (GRA). The analysis systematically evaluates the impact of the flow rate, coolant ratio, and fan speed on key performance metrics, including the hybrid temperature difference, bulk mean temperature, heat energy, Reynolds number, convective heat transfer coefficient, and overall heat transfer coefficient. The findings suggested that the flow rate and coolant ratio are critical factors influencing the system efficiency, while the integration of time bound Peltier heat sink reduces the impact of fan speed to stationary level. The GRA analysis identified the optimal operating conditions of an LPH flow rate of 19, coolant ratio of 70%, and fan speed of 3 m/s, striking a balance between maximized heat transfer and favourable temperature difference. The Taguchi interaction plots and Machine learning visualization tool Heat Map are generated to show the correlation between variable. Significant improvements in cooling performance and energy efficiency were achieved at optimal interaction of flow rate and coolant ratio. This research provides valuable insights for engineers in designing and configuring efficient thermal management systems for future hybrid vehicles, showcasing the potential of Peltier-based cooling systems in advancing automotive technology.