The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Jin Huang - One of the best experts on this subject based on the ideXlab platform.
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energy management strategy for fuel cell battery ultracapacitor Hybrid Vehicle based on fuzzy logic
International Journal of Electrical Power & Energy Systems, 2012Co-Authors: Qi Li, Shukui Liu, Yankun Li, Weirong Chen, Jin HuangAbstract:Abstract In order to enhance the fuel economy of Hybrid Vehicle and increase the mileage of continuation of journey, a fuzzy logic control is utilized to design energy management strategies for fuel cell/battery (FC + B) Hybrid Vehicle and fuel cell/battery/ultra-capacitor (FC + B + UC) Hybrid Vehicle. The models of Hybrid Vehicle for FC + B and FC + B + UC structure are developed by electric Vehicle simulation software ADVISOR which uses a Hybrid backward/forward approach. The results demonstrate that the proposed control strategy can satisfy the power requirement for four standard driving cycles and achieve the power distribution among various power sources. The comprehensive comparisons with the power tracking control strategy which is wide adopted in ADVISOR verify that the proposed control strategy has better rationality and validity in terms of fuel economy and dynamic property in four standard driving cycles. Therefore, the proposed strategy will provide a novel approach for the advanced energy management system of Hybrid Vehicle.
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Energy management strategy for fuel cell/battery/ultracapacitor Hybrid Vehicle based on fuzzy logic
International Journal of Electrical Power & Energy Systems, 2012Co-Authors: Weirong Chen, Shukui Liu, Jin HuangAbstract:Abstract In order to enhance the fuel economy of Hybrid Vehicle and increase the mileage of continuation of journey, a fuzzy logic control is utilized to design energy management strategies for fuel cell/battery (FC + B) Hybrid Vehicle and fuel cell/battery/ultra-capacitor (FC + B + UC) Hybrid Vehicle. The models of Hybrid Vehicle for FC + B and FC + B + UC structure are developed by electric Vehicle simulation software ADVISOR which uses a Hybrid backward/forward approach. The results demonstrate that the proposed control strategy can satisfy the power requirement for four standard driving cycles and achieve the power distribution among various power sources. The comprehensive comparisons with the power tracking control strategy which is wide adopted in ADVISOR verify that the proposed control strategy has better rationality and validity in terms of fuel economy and dynamic property in four standard driving cycles. Therefore, the proposed strategy will provide a novel approach for the advanced energy management system of Hybrid Vehicle.
Huei Peng - One of the best experts on this subject based on the ideXlab platform.
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Modeling and control of a power-split Hybrid Vehicle
IEEE Transactions on Control Systems Technology, 2008Co-Authors: Jinming Liu, Huei PengAbstract:Toyota Hybrid system (THS) is used in the current best selling Hybrid Vehicle on the market-the Toyota Prius. This Hybrid system contains a power-split planetary gear system which combines the benefits of series and parallel Hybrid Vehicles. In this paper, we developed a dynamic model of the THS powertrain and then apply it for model-based control development. Two control algorithms are introduced: one based on the stochastic dynamic programming method, and the other based on the equivalent consumption minimization strategy. Both approaches determine the engine power based on the overall Vehicle efficiency and apply the electrical machines to optimize the engine operation. The performance of these two algorithms is assessed by comparing against the dynamic programming results, which are non-causal but provide theoretical benchmarks for other implementable control algorithms.
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system level model and stochastic optimal control for a pem fuel cell Hybrid Vehicle
Journal of Dynamic Systems Measurement and Control-transactions of The Asme, 2006Co-Authors: Chanchiao Lin, Min Joong Kim, Huei Peng, Jessy W. GrizzleAbstract:System-level modeling and control strategy development for a fuel cell Hybrid Vehicle (FCHV) are presented in this paper. A reduced-order fuel cell model is created to accurately predict the fuel cell system efficiency while retaining dynamic effects of important variables. The fuel cell system model is then integrated with a DC/DC converter, a Li-ion battery, an electric drive, and tire/Vehicle dynamics to form an FCHV. In order to optimize the power management strategy of the FCHV, we develop a stochastic design approach based on the Markov chain modeling and stochastic dynamic programming (SDP). The driver demand is modeled as a Markov process to represent the future uncertainty under diverse driving conditions. The infinite-horizon SDP solution generates a stationary state-feedback control policy to achieve optimal power management between the fuel cell system and battery. Simulation results over different driving cycles are presented to demonstrate the effectiveness of the proposed stochastic approach.
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testing modeling and control of a fuel cell Hybrid Vehicle
American Control Conference, 2005Co-Authors: Min Joong Kim, Chanchiao Lin, E Stamos, Huei Peng, D. TranAbstract:A comprehensive procedure for testing, modeling, and control design of a fuel cell Hybrid Vehicle (FCHV) is presented in this paper. The subsystems are modeled based on lab testing and in-field Vehicle testing results from the DaimlerChrysler Natrium prototype Vehicle. An FC-VESIM (fuel cell Hybrid Vehicle simulation) model is then developed based on the experimental data. The power management control algorithm for the FCHV is subsequently developed based on the stochastic dynamic programming (SDP) technique, which produces an optimal policy for a given probability distribution of the Vehicle power demand.
Weirong Chen - One of the best experts on this subject based on the ideXlab platform.
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energy management strategy for fuel cell battery ultracapacitor Hybrid Vehicle based on fuzzy logic
International Journal of Electrical Power & Energy Systems, 2012Co-Authors: Qi Li, Shukui Liu, Yankun Li, Weirong Chen, Jin HuangAbstract:Abstract In order to enhance the fuel economy of Hybrid Vehicle and increase the mileage of continuation of journey, a fuzzy logic control is utilized to design energy management strategies for fuel cell/battery (FC + B) Hybrid Vehicle and fuel cell/battery/ultra-capacitor (FC + B + UC) Hybrid Vehicle. The models of Hybrid Vehicle for FC + B and FC + B + UC structure are developed by electric Vehicle simulation software ADVISOR which uses a Hybrid backward/forward approach. The results demonstrate that the proposed control strategy can satisfy the power requirement for four standard driving cycles and achieve the power distribution among various power sources. The comprehensive comparisons with the power tracking control strategy which is wide adopted in ADVISOR verify that the proposed control strategy has better rationality and validity in terms of fuel economy and dynamic property in four standard driving cycles. Therefore, the proposed strategy will provide a novel approach for the advanced energy management system of Hybrid Vehicle.
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Energy management strategy for fuel cell/battery/ultracapacitor Hybrid Vehicle based on fuzzy logic
International Journal of Electrical Power & Energy Systems, 2012Co-Authors: Weirong Chen, Shukui Liu, Jin HuangAbstract:Abstract In order to enhance the fuel economy of Hybrid Vehicle and increase the mileage of continuation of journey, a fuzzy logic control is utilized to design energy management strategies for fuel cell/battery (FC + B) Hybrid Vehicle and fuel cell/battery/ultra-capacitor (FC + B + UC) Hybrid Vehicle. The models of Hybrid Vehicle for FC + B and FC + B + UC structure are developed by electric Vehicle simulation software ADVISOR which uses a Hybrid backward/forward approach. The results demonstrate that the proposed control strategy can satisfy the power requirement for four standard driving cycles and achieve the power distribution among various power sources. The comprehensive comparisons with the power tracking control strategy which is wide adopted in ADVISOR verify that the proposed control strategy has better rationality and validity in terms of fuel economy and dynamic property in four standard driving cycles. Therefore, the proposed strategy will provide a novel approach for the advanced energy management system of Hybrid Vehicle.
Shukui Liu - One of the best experts on this subject based on the ideXlab platform.
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energy management strategy for fuel cell battery ultracapacitor Hybrid Vehicle based on fuzzy logic
International Journal of Electrical Power & Energy Systems, 2012Co-Authors: Qi Li, Shukui Liu, Yankun Li, Weirong Chen, Jin HuangAbstract:Abstract In order to enhance the fuel economy of Hybrid Vehicle and increase the mileage of continuation of journey, a fuzzy logic control is utilized to design energy management strategies for fuel cell/battery (FC + B) Hybrid Vehicle and fuel cell/battery/ultra-capacitor (FC + B + UC) Hybrid Vehicle. The models of Hybrid Vehicle for FC + B and FC + B + UC structure are developed by electric Vehicle simulation software ADVISOR which uses a Hybrid backward/forward approach. The results demonstrate that the proposed control strategy can satisfy the power requirement for four standard driving cycles and achieve the power distribution among various power sources. The comprehensive comparisons with the power tracking control strategy which is wide adopted in ADVISOR verify that the proposed control strategy has better rationality and validity in terms of fuel economy and dynamic property in four standard driving cycles. Therefore, the proposed strategy will provide a novel approach for the advanced energy management system of Hybrid Vehicle.
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Energy management strategy for fuel cell/battery/ultracapacitor Hybrid Vehicle based on fuzzy logic
International Journal of Electrical Power & Energy Systems, 2012Co-Authors: Weirong Chen, Shukui Liu, Jin HuangAbstract:Abstract In order to enhance the fuel economy of Hybrid Vehicle and increase the mileage of continuation of journey, a fuzzy logic control is utilized to design energy management strategies for fuel cell/battery (FC + B) Hybrid Vehicle and fuel cell/battery/ultra-capacitor (FC + B + UC) Hybrid Vehicle. The models of Hybrid Vehicle for FC + B and FC + B + UC structure are developed by electric Vehicle simulation software ADVISOR which uses a Hybrid backward/forward approach. The results demonstrate that the proposed control strategy can satisfy the power requirement for four standard driving cycles and achieve the power distribution among various power sources. The comprehensive comparisons with the power tracking control strategy which is wide adopted in ADVISOR verify that the proposed control strategy has better rationality and validity in terms of fuel economy and dynamic property in four standard driving cycles. Therefore, the proposed strategy will provide a novel approach for the advanced energy management system of Hybrid Vehicle.
Ajay K. Prasad - One of the best experts on this subject based on the ideXlab platform.
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drive train simulator for a fuel cell Hybrid Vehicle
Journal of Power Sources, 2008Co-Authors: Darren Brown, Marcus Alexander, Doug Brunner, Suresh G. Advani, Ajay K. PrasadAbstract:Abstract The model formulation, development process, and experimental validation of a new Vehicle powertrain simulator called LFM (Light, Fast, and Modifiable) are presented. The existing powertrain simulators were reviewed and it was concluded that there is a need for a new, easily modifiable simulation platform that will be flexible and sufficiently robust to address a variety of Hybrid Vehicle platforms. First, the structure and operating principle of the LFM simulator are presented, followed by a discussion of the subsystems and input/output parameters. Finally, a validation exercise is presented in which the simulator's inputs were specified to represent the University of Delaware's fuel cell Hybrid transit Vehicle and “driven” using an actual drive cycle acquired from it. Good agreement between the output of the simulator and the physical data acquired by the Vehicle's on-board sensors indicates that the simulator constitutes a powerful and reliable design tool.
