Journal ArticleDOI
Fuzzy logic control for parallel hybrid vehicles
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TLDR
A fuzzy logic controller is developed for hybrid vehicles with parallel configuration to effectively determine the split between the two powerplants: electric motor and internal combustion engine.Abstract:
In this paper, a fuzzy logic controller is developed for hybrid vehicles with parallel configuration. Using the driver command, the state of charge of the energy storage, and the motor/generator speed, a set of rules have been developed, in a fuzzy controller, to effectively determine the split between the two powerplants: electric motor and internal combustion engine. The underlying theme of the fuzzy rules is to optimize the operational efficiency of all components, considered as one system. Simulation results were used to assess the performance of the controller. A forward-looking hybrid vehicle model was used for implementation and simulation of the controller. Potential fuel economy improvement is shown by using fuzzy logic, relative to other controllers, which maximize only the efficiency of the engine.read more
Citations
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Journal ArticleDOI
Power management strategy for a parallel hybrid electric truck
TL;DR: The design procedure starts by defining a cost function, such as minimizing a combination of fuel consumption and selected emission species over a driving cycle, and dynamic programming is utilized to find the optimal control actions including the gear-shifting sequence and the power split between the engine and motor while subject to a battery SOC-sustaining constraint.
Journal ArticleDOI
A review of energy sources and energy management system in electric vehicles
Siang Fui Tie,Chee Wei Tan +1 more
TL;DR: In this article, the state-of-the-art of the energy sources, storage devices, power converters, low-level control energy management strategies and high supervisor control algorithms used in electric vehicles are reviewed.
Journal ArticleDOI
Control Strategies for Hybrid Electric Vehicles: Evolution, Classification, Comparison, and Future Trends
TL;DR: This paper classifies and extensively overviews the state-of-the-art control strategies for HEVs, establishing a basis for comparing available methods and helping devoted researchers choose the right track.
Journal ArticleDOI
A Stochastic Optimal Control Approach for Power Management in Plug-In Hybrid Electric Vehicles
TL;DR: This paper uses stochastic dynamic programming to optimize PHEV power management over a distribution of drive cycles, rather than a single cycle, thereby systematically exploring the potential benefits of controlled charge depletion over aggressive charge depletion followed by charge sustenance.
Proceedings ArticleDOI
A stochastic control strategy for hybrid electric vehicles
TL;DR: In this paper, a stochastic dynamic programming (SDP) approach was used to obtain the optimal supervisory control strategy for hybrid vehicles with random Markov processes. But the resulting control strategy was often inherently cycle-beating and lacked a guaranteed level of optimality.
References
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Journal ArticleDOI
Fuzzy identification of systems and its applications to modeling and control
T. Takagi,Michio Sugeno +1 more
TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Journal ArticleDOI
Fuzzy logic in control systems: fuzzy logic controller. II
TL;DR: The basic aspects of the FLC (fuzzy logic controller) decision-making logic are examined and several issues, including the definitions of a fuzzy implication, compositional operators, the interpretations of the sentence connectives 'and' and 'also', and fuzzy inference mechanisms, are investigated.
Journal ArticleDOI
Application of fuzzy algorithms for control of simple dynamic plant
TL;DR: In this article, the authors describe a scheme in which a fuzzy algorithm is used to control plant, in this case, a laboratory-built steam engine, implemented as an interpreter of a set of rules expressed as fuzzy conditional statements.
Book
An Introduction to Fuzzy Control
TL;DR: Fuzzy controllers are a class of knowledge based controllers using artificial intelligence techniques with origins in fuzzy logic that can be found either as stand-alone control elements or as int ...
Journal ArticleDOI
ADVISOR 2.1: a user-friendly advanced powertrain simulation using a combined backward/forward approach
TL;DR: ADVISOR 2.1 as mentioned in this paper is the latest version of the National Renewable Energy Laboratory's advanced vehicle simulator, which is designed to be accurate, fast, flexible, easily sharable, and easy to use.