Constrained Optimal Fuel Consumption of HEVs under Observational Noise
NeutralArtificial Intelligence
This article discusses the challenges of achieving optimal fuel consumption in hybrid electric vehicles (HEVs) when faced with observational noise in state-of-charge measurements. It builds on previous research that used a constrained reinforcement learning framework, highlighting the need to adapt to real-world conditions where sensor inaccuracies can impact performance.
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