<div class="csl-bib-body">
<div class="csl-entry">Büyüker, B. Ç., Ferrara, A., & Hametner, C. (2022). Predictive Battery Cooling in Heavy-Duty Fuel Cell Electric Vehicles. In <i>IFAC-PapersOnLine</i> (pp. 304–310). Elsevier BV. https://doi.org/10.1016/j.ifacol.2022.10.301</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/136092
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dc.description.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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dc.language.iso
en
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dc.subject
Battery Thermal Management System
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dc.subject
Fuel Cell Electric Vehicles
en
dc.subject
Model Predictive Control
en
dc.subject
Predictive Cooling Strategies
en
dc.subject
Battery Thermal Model
en
dc.title
Predictive Battery Cooling in Heavy-Duty Fuel Cell Electric Vehicles