Journal ArticleDOI
Online energy management strategy of fuel cell hybrid electric vehicles based on data fusion approach
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Experimental comparison results show that, the proposed PSVM-DS based online controller can achieve a relatively stable operation and a higher efficiency of fuel cell system in real driving cycles.About:
This article is published in Journal of Power Sources.The article was published on 2017-10-31. It has received 149 citations till now. The article focuses on the topics: Fuzzy logic & Control theory.read more
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Energy management of hybrid electric vehicles: A review of energy optimization of fuel cell hybrid power system based on genetic algorithm
TL;DR: This paper analyzes and summarizes the optimization effect of genetic algorithm in various energy management strategies, aiming to analyze and select the optimization rules and parameters, optimization objects and optimization objectives.
Journal ArticleDOI
A comprehensive review on hybrid power system for PEMFC-HEV: Issues and strategies
TL;DR: This paper makes a deep study of the current PEMFC-HEV hybrid system model, and the EMS developed by the researchers, including faster dynamic response, longer service lifetime, economic optimization, and high efficiency for the PemFC system.
Journal Article
Interdependence between safety-control policy and multiple-sensor
TL;DR: The author explores the application of the D-S theory in system reliability and safety and proves that a unified combination rule for fusing information on plant states given by independent knowledge sources such as sensors or human operators is developed.
Journal ArticleDOI
Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning
TL;DR: A deep reinforcement learning (DRL)-based EMS is designed such that it can learn to select actions directly from the states without any prediction or predefined rules in HEVs, and the online learning architecture is proved to be effective.
Journal ArticleDOI
A survey on driving prediction techniques for predictive energy management of plug-in hybrid electric vehicles
TL;DR: This paper indicates suitable application scenarios for each prediction algorithm and summarizes potential approaches for handling the prediction inaccuracies, which will help prospective designers to select proper DPTs according to different applications and contribute to the further performance enhancements of PEMSs for hybrid electric vehicles (HEVs) and plug-in hybridelectric vehicles (PHEVs).
References
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Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
TL;DR: Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
Book
A mathematical theory of evidence
TL;DR: This book develops an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions.
Journal ArticleDOI
Probability Estimates for Multi-class Classification by Pairwise Coupling
TL;DR: In this paper, the authors present two approaches for obtaining class probabilities, which can be reduced to linear systems and are easy to implement, and show conceptually and experimentally that the proposed approaches are more stable than the two existing popular methods: voting and the method by Hastie and Tibshirani (1998).
Journal ArticleDOI
Energy-management system for a hybrid electric vehicle, using ultracapacitors and neural networks
TL;DR: A very efficient energy-management system for hybrid electric vehicles (HEVs), using neural networks (NNs), was developed and tested, and the increase in range was around 5.3% in city tests, however, when optimal control with NN was used, this figure increased to 8.9%.