AAC 2019 Paper Abstract

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Paper TuBT1.2

Wei, Caiyang (Eindhoven University of Technology), Hofman, Theo (Technische Universiteit Eindhoven), Ilhan Caarls, Esin (Bosch Transmission Technology), van Iperen, Rokus (Bosch Transmission Technology)

Zone Model Predictive Control for Battery Thermal Management Including Battery Aging and Brake Energy Recovery in Electrified Powertrains

Scheduled for presentation during the Regular Session "Control & Estimation III : Energy sources" (TuBT1), Tuesday, June 25, 2019, 15:05−15:25, Chambord

9th IFAC International Symposium on Advances in Automotive Control, June 23-27, 2019, Orléans, France

This information is tentative and subject to change. Compiled on March 28, 2024

Keywords Battery Model and Battery Control, XEV (HEV,EV,FCEV,etc.)/Solar-Powered Vehicles

Abstract

This paper proposes a detailed battery thermal management system for electrified powertrains. A battery aging model consisting of capacity fade and power fade sub-models is built to adjust state of charge estimation and heat generation. The trade-off between the benefit of recuperating braking energy and the cost of additional cooling power is investigated. It is found that the recovery ratio depends on the efficiency of the air conditioning system and the intensity and density of the available braking power. A zone model predictive control approach is developed to maintain the battery temperature within its optimal operating range with minimum power consumption. Remarkable energy consumption reduction can be achieved comparing to traditional controllers.

 

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