Multi-Mode Predictive Energy Management for Fuel Cell Hybrid Vehicle Using Markov

In this paper, a Markov decision method-primarily based multi-mode predictive strength control device for fuel mobile hybrid automobiles (FCHVs) is proposed. To improve gas efficiency and reduce emissions, the gadget seeks to optimize energy allocation between the gasoline cell stack and power garage components. The cautioned machine employs a Markov version to forecast destiny situations and operates in numerous modes depending on riding instances and power call for. This enables proactive decision-making. When estimating power requirements and allocating energy accurately, the version takes under consideration variables which include automobile speed, acceleration, and road grade. Dynamic programming is used to optimize a price characteristic that takes into account fuel usage, battery ageing, and machine performance. The ideal strength distribution for every mode is determined with the aid of contemplating the transition chances between riding situations. Compared to rule-based techniques, the system's effectiveness is validated by simulations and experiments, which show extra fuel efficiency and general performance. The device enables proactive choice-making via the use of the Markov version, which improves the usage of the to be had electricity resources and improves car performance. This study introduces a logo-new method for coping with strength in FCHVs that offers enormous upgrades in phrases of gasoline economic system and pollutants reduction.