On-line fuzzy energy management for hybrid fuel cell systems

Caux, Stéphane; Hankache, Walid; Fadel, Maurice; Hissel, Daniel

doi:10.1016/j.ijhydene.2009.11.108

Cited by 139 publications

(56 citation statements)

References 27 publications

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“…In the last decade, different energy management strategies for FCHEV power systems have been reported [18]- [23]. In [18] and [19], the system is appropriately controlled by a rule-based strategy; however, the performances of the energy system depend on previous experiences. In [22] and [23], the system is appropriately controlled by a model predictive control strategy and neural networks strategy, respectively.…”

Section: A Review Of Energy Management Strategy In Hev Energy Systemmentioning

confidence: 99%

See 1 more Smart Citation

Stability Analysis of FCHEV Energy System Using Frequency Decoupling Control Method

Dai¹,

Sun²,

Xie³

et al. 2017

Journal of Power Electronics

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Fuel cell (FC) is a promising power supply in electric vehicles (EV); however, it has poor dynamic performance and short service life. To address these shortcomings, a super capacitor (SC) is adopted as an auxiliary power supply. In this study, the frequency decoupling control method is used in electric vehicle energy system. High-frequency and low-frequency demand power is provided by SC and FC, respectively, which makes full use of two power supplies. Simultaneously, the energy system still has rapidity and reliability. The distributed power system (DPS) of EV requires DC-DC converters to achieve the desired voltage. The stability of cascaded converters must be assessed. Impedance-based methods are effective in the stability analysis of DPS. In this study, closed-loop impedances of interleaved half-bridge DC-DC converter and phase-shifted full-bridge DC-DC converter based on the frequency decoupling control method are derived. The closed-loop impedance of an inverter for permanent magnet synchronous motor based on space vector modulation control method is also derived. An improved Middlebrook criterion is used to assess and adjust the stability of the energy system. A theoretical analysis and simulation test are provided to demonstrate the feasibility of the energy management system and the control method.

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Section: A Review Of Energy Management Strategy In Hev Energy Systemmentioning

confidence: 99%

“…The open-and closed-loop impedances of the source converter are shown in Fig. 6 [25], the Z BVCC and Z BCCC of the system can be obtained using Equation (19). The Bode plots are shown in Fig.…”

Section: A Analysis and Adjustment Of The Energy System Stabilitymentioning

confidence: 99%

Stability Analysis of FCHEV Energy System Using Frequency Decoupling Control Method

Dai¹,

Sun²,

Xie³

et al. 2017

Journal of Power Electronics

View full text Add to dashboard Cite

show abstract

“…The power allocation methods are applied to define the power sources, and it can be categorized into rule-based and optimization approaches [10]. researchers have investigated the application of various methods including fuzzy logic strategy [11], sliding mode control [12], model predictive control [13], load-following mode control [14], dynamic programming (DP) [15] and convex optimization strategies [16], Equivalent Consumption Minimization Strategies (ECMS) [17] and Pontryagin's Minimum Principle (PMP) strategies [18]. For the component sizing problems, Sundstrom,et al [19] explored the battery sizing problem of a FCHV by DP under three type of cycles and found the optimal battery size is dependent on the cycle, the vehicle weight, etc.…”

Section: Introductionmentioning

confidence: 99%

Power Component Sizing Based on Power Allocation Strategy for a Fuel Cell/Battery Hybrid Tram

Zhang¹,

Xu²,

Li³

et al. 2016

Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)

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“…There are some control strategies in fuel cell hybrid vehicle (FCHV), such as fuzzy control and state of charge (SOC) control [6][7][8], which refer to energy management and SOC balance. This paper employs control strategy based on power following, applying vehicle simulation software ADVISOR and GA to conduct vehicle simulation, comparing its results with the real vehicle testing to analyze the mini FCHV; it aims to find out the appropriate optimization parameters.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Test of a Fuel Cell Hybrid Golf Cart

Liang

Jian

2014

Journal of Electrical and Computer Engineering

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This paper establishes the simulation model of fuel cell hybrid golf cart (FCHGC), which applies the non-GUI mode of the Advanced Vehicle Simulator (ADVISOR) and the genetic algorithm (GA) to optimize it. Simulation of the objective function is composed of fuel consumption and vehicle dynamic performance; the variables are the fuel cell stack power sizes and the battery numbers. By means of simulation, the optimal parameters of vehicle power unit, fuel cell stack, and battery pack are worked out. On this basis, GUI mode of ADVISOR is used to select the rated power of vehicle motor. In line with simulation parameters, an electrical golf cart is refitted by adding a 2 kW hydrogen air proton exchange membrane fuel cell (PEMFC) stack system and test the FCHGC. The result shows that the simulation data is effective but it needs improving compared with that of the real cart test.

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On-line fuzzy energy management for hybrid fuel cell systems

Cited by 139 publications

References 27 publications

Stability Analysis of FCHEV Energy System Using Frequency Decoupling Control Method

Stability Analysis of FCHEV Energy System Using Frequency Decoupling Control Method

Power Component Sizing Based on Power Allocation Strategy for a Fuel Cell/Battery Hybrid Tram

Simulation and Test of a Fuel Cell Hybrid Golf Cart

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