2021Strojniški vestnik – Journal of Mechanical EngineeringOpen access

HIL Evaluation of a Novel Real-time Energy Management System for an HEV with a Continuously Variable Transmission

Amir Taghavipour, Ali Alipour

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Abstract

One of the most important challenges facing automotive engineers is reducing vehicle fuel consumption and improving the drivability index. Modern hybrid electric powertrains play an important role in reducing fuel consumption. Continuously variable transmission (CVT) is an automatic transmission that can change the gear ratio seamlessly using a belt and pulleys. CVT performs with infinite gear ratios. Controlling and determining the optimal gear ratio, especially in a complex hybrid powertrain, is a major challenge. Therefore, a multi-parametric model predictive controller with real-time implementation capability is proposed that can handle the energy management task concurrently with gear shifting strategy in a parallel pre-transmission hybrid electric vehicle. The proposed controller hardware-in-the-loop (HIL) validation procedure on the high-fidelity Autonomie model shows significant improvement in fuel economy while maintaining drivability in three different driving schedules. HIL evaluation guarantees the real-time capability and the proposed controller readiness to be implemented to real-world control hardware.

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One of the most important challenges facing automotive engineers is reducing vehicle fuel consumption and improving the drivability index. Modern hybrid electric powertrains play an important role in reducing fuel consumption. Continuously variable transmission (CVT) is an automatic transmission that can change the gear ratio seamlessly using a belt and pulleys. CVT performs with infinite gear ratios. Controlling and determining the optimal gear ratio, especially in a complex hybrid powertrain, is a major challenge. Therefore, a multi-parametric model predictive controller with real-time implementation capability is proposed that can handle the energy management task concurrently with gear shifting strategy in a parallel pre-transmission hybrid electric vehicle. The proposed controller hardware-in-the-loop (HIL) validation procedure on the high-fidelity Autonomie model shows significant improvement in fuel economy while maintaining drivability in three different driving schedules. HIL evaluation guarantees the real-time capability and the proposed controller readiness to be implemented to real-world control hardware.

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Available abstract

One of the most important challenges facing automotive engineers is reducing vehicle fuel consumption and improving the drivability index. Modern hybrid electric powertrains play an important role in reducing fuel consumption. Continuously variable transmission (CVT) is an automatic transmission that can change the gear ratio seamlessly using a belt and pulleys. CVT performs with infinite gear ratios. Controlling and determining the optimal gear ratio, especially in a complex hybrid powertrain, is a major challenge. Therefore, a multi-parametric model predictive controller with real-time implementation capability is proposed that can handle the energy management task concurrently with gear shifting strategy in a parallel pre-transmission hybrid electric vehicle. The proposed controller hardware-in-the-loop (HIL) validation procedure on the high-fidelity Autonomie model shows significant improvement in fuel economy while maintaining drivability in three different driving schedules. HIL evaluation guarantees the real-time capability and the proposed controller readiness to be implemented to real-world control hardware.

Key concepts: Powertrain, Continuously variable transmission, Manual transmission, Automotive engineering, Controller (irrigation), Automotive industry, Automatic transmission, Transmission (telecommunications)

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