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<p>The increased popularity of electric vehicles (EVs) created an understanding that energy-efficient auxiliary systems, such as air conditioning (AC), are urgently needed to better preserve battery health and driving range. Traditional AC units have fixed operating conditions without any active control to mitigate energy losses, calling for intelligent control for dynamic operation. Here, a new framework has been presented that combines Sequential Quadratic Programming (SQP) and a new version of Banyan Tree Growth Optimizer (ABTGO) to optimize the efficiency deployment of frequency-variable heat pump (HP) AC systems for the EVs. ABTGO, which derives its inspiration from banyan tree growth, is capable of performing good quality global exploration while SQP focuses on refining the solutions locally, optimizing the compressor and fan frequencies for an accurate operating condition. They performed simulations to demonstrate the overall power consumption savings up to 28.6% for the proposed method without degrading efficiency or thermal comfort over the best performing state-of-the-art methods. Additionally, the suggested model tackles gradually converging near-optimum exploration-exploitation trade-offs offered by current methods by dynamically adapting to conditions in real life. The research not only enhances environmental sustainability of EVs with an enhanced driving range but also redesigns optimal AC system design, and it formulates a model extendable to a wide range of operating conditions.</p>

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Optimized energy-saving design of frequency-variable heat pump air conditioning systems in electric vehicles using an advanced Banyan tree growth optimizer

  • 期刊论文

  • 发表日期：

    2026年2月5日

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  • Wenshi Gou

摘要

The increased popularity of electric vehicles (EVs) created an understanding that energy-efficient auxiliary systems, such as air conditioning (AC), are urgently needed to better preserve battery health and driving range. Traditional AC units have fixed operating conditions without any active control to mitigate energy losses, calling for intelligent control for dynamic operation. Here, a new framework has been presented that combines Sequential Quadratic Programming (SQP) and a new version of Banyan Tree Growth Optimizer (ABTGO) to optimize the efficiency deployment of frequency-variable heat pump (HP) AC systems for the EVs. ABTGO, which derives its inspiration from banyan tree growth, is capable of performing good quality global exploration while SQP focuses on refining the solutions locally, optimizing the compressor and fan frequencies for an accurate operating condition. They performed simulations to demonstrate the overall power consumption savings up to 28.6% for the proposed method without degrading efficiency or thermal comfort over the best performing state-of-the-art methods. Additionally, the suggested model tackles gradually converging near-optimum exploration-exploitation trade-offs offered by current methods by dynamically adapting to conditions in real life. The research not only enhances environmental sustainability of EVs with an enhanced driving range but also redesigns optimal AC system design, and it formulates a model extendable to a wide range of operating conditions.