20231115 · Energy management strategies (EMSs) are crucial for the hydrogen economy and energy component lifetimes of fuel cell hybrid electric unmanned aerial vehicles (UAVs). Reinforcement learning (RL)-based schemes have been a hotspot for EMSs, but most of RL-based EMSs focus on the energy-saving performance and rarely
20171130 · To make the NN-based energy management strategy more flexible, this paper proposes a controllable NN for optimal energy management of fuel cell hybrid electric vehicles. Inspired by the equivalent factor in the Equivalent Consumption Minimization Strategy (ECMS), we introduce an adjustable target variable for the final state as an input
202199 · This paper proposes an energy management strategy for a fuel cell (FC) hybrid power system based on dynamic programming and state machine strategy, which
2024415 · An effective energy management strategy (EMS) is crucial to reduce the usage cost of FCHEV and enhance SOC maintenance ability. This study establishes
201581 · This paper presents a comparative study of two energy management strategies for a hybrid power source composed of a fuel cell and a supercapacitor. The strategies are based on linear and sliding mode control techniques, and aim to optimize the efficiency and performance of the hybrid system. The paper also provides simulation and
2024410 · Providing a systematic review of fuel cell-based hybrid energy systems • Reviewing fuel cell integration with renewable sources and storage systems under
2024418 · Abstract. For hydrogen fuel cell vehicles, energy management strategies (EMS) are vital for balancing fuel cell and battery power, limiting fuel cell power, maintaining state of charge (SOC) fluctuation range and mitigating degradation. Reinforcement learning-based EMS, especially using deep Q-network (DQN) and deep deterministic policy
2012614 · American Institute of Aeronautics and Astronautics 12700 Sunrise Valley Drive, Suite 200 Reston, VA 20191-5807 703.264.7500
2018119 · Abstract: This paper presents a nonmyopic energy management strategy (EMS) for controlling multiple energy flow in fuel cell hybrid vehicles. The control problem
5 · @article{Fu2024EnergyMS, title={Energy management strategy for long-life fuel cell hybrid power systems based on improved whale optimization algorithm},
2023519 · Energy management of a fuel cell/ultra-capacitor hybrid electric vehicle under uncertainty based on CO-SNN method. 2024, Journal of Energy Storage. Show abstract. This manuscript proposes a hybrid technique for effective energy management in hybrid electric vehicles with ultra-capacitors and fuel cells. The proposed hybrid
Abstract: Aiming at the problem of the loss of the ship''s propulsion system caused by the load fluctuation under the complex working conditions of the ship, a fuel cell ship energy
201111 · 1.. IntroductionCurrently, most of the energy demand in the world is met by fossil and nuclear power plants. A small part is drawn from renewable energy technologies such as wind, solar, fuel cell, biomass and geothermal energy [1], [2].Wind energy, solar energy and fuel cells have experienced a remarkably rapid growth in the past ten years
5 · His research interests include fuel cell control and energy management technology, fuel cell power generation systems, and intelligent algorithm. Qihong Chen.
3 · In order to solve the energy management problems of an electric vehicle based on fuel cell and ultracapacitor. Firstly, the models of fuel cell and ultracapacitor are
202151 · Energy management control strategy is one of the key technologies in the. development of extended -range fuel cell vehicles. During the use of vehicles, fuel cell. performance will decline, which
202412 · An excellent energy management strategy not only distributes energy rationally between the fuel cell and the power battery, but also plays an important role in reducing hydrogen consumption, increasing range and extending battery life [7, 8].
2022830 · Developing an energy management strategy (EMS) is an important requirement to satisfy the load power demand for a proton-exchange membrane fuel cell (PEMFC) hybrid system under different
2023111 · Data-driven intelligent energy management strategy (EMS) helps to further improve the performance and efficiency of fuel cell hybrid electric bus (FCHEB). However, most deep reinforcement learning (DRL) algorithms suffer from disadvantages such as overestimation and poor training stability, which limit the optimization effectiveness of the