Abstract
Preserving high-voltage battery pack lifetime represents a key issue in hybrid electric vehicles (HEVs). Temperature has remarkably major impacts on battery lifetime and implementing HEV thermal and energy management approaches to enhance fuel economy while preserving battery lifetime at various temperatures still represents an open challenge. This paper introduces an optimization driven methodology to tune the parameters of thermal and energy on-board rule-based control approaches of a parallel through-the-road plug-in HEV. Particle swarm optimization is implemented to this end and the calibration objective involves minimizing HEV operative costs concerning energy consumption and battery degradation over the entire vehicle lifetime for various ambient temperatures, driving conditions, payload conditions, and cabin conditioning system states. Numerical models are implemented that can estimate the evolution over time of the state of charge, state of health, and temperature of HEV high-voltage battery packs. Obtained results suggest that the calibrated thermal and energy management strategy tends to reduce pure electric operation as the ambient temperature progressively increases beyond 30 °C. The consequent longer internal combustion engine operation entails a gradual increase in the overall vehicle energy demand. At a 36 °C ambient temperature, the HEV consumes 2.3 times more energy compared with the 15 °C reference value. Moreover, activating the cabin conditioning system seems beneficial for overall plug-in HEV energy consumption at high ambient temperatures. The presented methodology can contribute to easing and accelerating the development process for energy and thermal management systems of HEVs.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
12 articles.
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