AAC 2022 Paper Abstract

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Paper TuBT4.2

Büyüker, Banu Cicek (TU Wien), Ferrara, Alessandro (TU Wien), Hametner, Christoph (Vienna University of Technology)

Predictive Battery Cooling in Heavy-Duty Fuel Cell Electric Vehicles

Scheduled for presentation during the Regular Session "Fuel Cell and Alternative Energy Vehicles" (TuBT4), Tuesday, August 30, 2022, 15:20−15:40, Pfahl Hall 140

10th IFAC International Symposium on Advances in Automotive Control, August 28-31, 2022, Columbus, Ohio, USA

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

Keywords Battery thermal management systems, Battery management systems, Energy management for XEV

Abstract

In electric vehicles, it is essential to prevent battery overheating due to excessive ohmic losses or inadequate cooling. Indeed, the temperature of battery systems significantly impacts their performance, lifetime, and safety. This paper proposes a predictive cooling optimization method for the battery thermal management system of heavy-duty fuel cell electric vehicles. The predictive cooling strategy is based on a model predictive control (MPC) formulation to maintain the battery temperature in its optimal range (to increase efficiency) and avoid high-temperature peaks (to increase lifetime and safety). The predictive thermal management relies on the ohmic losses forecast provided by a predictive energy management system. Simulations of a real-world driving cycle validate the proposed MPC and assess the impact of the predictive horizon length, which is critical for thermal management performance. The comparison against a simple hysteresis control strategy highlights the significant benefits of the proposed MPC for higher battery efficiency and lifetime.

 

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