In electric vehicle applications, batteries are usually packed in modules to satisfy the energy and power demand. To facilitate the thermal management of a battery pack, a model-based observer could be designed to estimate the temperature distribution across the pack. Nevertheless, cost target in industry practice drives the number of temperature sensors in a pack to a number that is not sufficient to yield observability of all the temperature states. This paper focuses on formulating the observer design and sensor deployment strategy that could achieve the optimal observer performance under the frugal sensor allocation. The considered observer performance is the estimation errors induced by model and sensor uncertainty. The observer aims at minimizing the worst-case estimation errors under bounded model and sensor uncertainty.

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