Development of Machine Learning Methods in Hybrid Energy Storage Systems in Electric Vehicles
Open Access
- 15 January 2022
- journal article
- research article
- Published by Hindawi Limited in Mathematical Problems in Engineering
- Vol. 2022, 1-8
- https://doi.org/10.1155/2022/3693263
Abstract
The hybrid energy storage systems are a practical tool to solve the issues in single energy storage systems in terms of specific power supply and high specific energy. These systems are especially applicable in electric and hybrid vehicles. Applying a dynamic and coherent strategy plays a key role in managing a hybrid energy storage system. The data obtained while driving and information collected from energy storage systems can be used to analyze the performance of the provided energy management method. Most existing energy management models follow predetermined rules that are unsuitable for vehicles moving in different modes and conditions. Therefore, it is so advantageous to provide an energy management system that can learn from the environment and the driving cycle and send the needed data to a control system for optimal management. In this research, the machine learning method and its application in increasing the efficiency of a hybrid energy storage management system are applied. In this regard, the energy management system is designed based on machine learning methods so that the system can learn to take the necessary actions in different situations directly and without the use of predicted select and run the predefined rules. The advantage of this method is accurate and effective control with high efficiency through direct interaction with the environment around the system. The numerical results show that the proposed machine learning method can achieve the least mean square error in all strategies.Keywords
This publication has 33 references indexed in Scilit:
- Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicleApplied Energy, 2018
- A deep reinforcement learning framework for optimizing fuel economy of hybrid electric vehiclesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2018
- Data-Driven Reinforcement Learning–Based Real-Time Energy Management System for Plug-In Hybrid Electric VehiclesTransportation Research Record: Journal of the Transportation Research Board, 2016
- Reinforcement Learning of Adaptive Energy Management With Transition Probability for a Hybrid Electric Tracked VehicleIEEE Transactions on Industrial Electronics, 2015
- Power management for Plug-in Hybrid Electric Vehicles using Reinforcement Learning with trip informationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- An overview of fuel cell technology: Fundamentals and applicationsRenewable and Sustainable Energy Reviews, 2014
- Trip-Oriented Energy Management Control Strategy for Plug-In Hybrid Electric VehiclesIEEE Transactions on Control Systems Technology, 2013
- Characteristics of electrical energy storage technologies and their applications in buildingsRenewable and Sustainable Energy Reviews, 2013
- Trip-oriented Energy Management Control strategy for plug-in hybrid electric vehiclesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- A Reinforcement-Learning-Based Assisted Power Management With QoR Provisioning for Human–Electric Hybrid BicycleIEEE Transactions on Industrial Electronics, 2011