Efficient experimental energy management operating for FC/battery/SC vehicles via hybrid Artificial Neural Networks-Passivity Based Control

The design of an efficient techno‐economic autonomous fuel cell hybrid electric vehicle (FCHEV) is a crucial challenge. This paper investigates the design of a near optimal PI controller for an automated FCHEV, where autonomy is expressed as efficient and robust tracking of a given reference speed trajectory without driver's intervention. An impartial comparison is introduced to illustrate the effectiveness of the proposed metaheuristic‐based optimal controllers in enhancing the system dynamic performance. The comprehensive optimization performance indicator is considered as a function of the vehicle dynamic characteristics while determining the optimal controller gains. In this paper, the proposed effective up‐to‐date metaheuristic techniques are the grey wolf optimization (GWO) as well as the artificial bee colony (ABC). Using MATLABTM/Simulink, numerical simulations clearly illustrate the efficiency of near‐optimal gains in the optimized tuning methodologies and the fixed manual one in realizing adequate velocity tracking. The simulation results demonstrate the superiority of both ABC and GWO rather than the manual controller for driving cycles of high acceleration and deceleration levels. In absence of these latter, the manual defined gain controller is considered sufficient. Through a comprehensive sensitivity analysis, the robustness of both metaheuristic‐based controllers is verified under diverse driving cycles of different operation features and nature. Despite GWO results in better dynamic characteristics, the ABC provides more economical feature with about 1.5% compared to manual system in extra urban driving cycle. However, manual‐controller has the minimum fuel cost under the United States driving cycle developed by the environmental protection agency as a New York city cycle (US EPA NYCC) and urban driving cycle (ECE). Ecologically, electric vehicles have an environmentally friendly effect especially when driven with green hydrogen. Autonomous vehicles, involving velocity control systems, would raise car share and provide more comfort.

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“…The stability of fuel cell based vehicles has been experimentally validated and theoretically proofed by Benmouna et al. [60].…”

Section: Multi‐optimization Framework With Metaheuristicsmentioning

confidence: 99%

Robust control for techno‐economic efficient energy management of fuel cell hybrid electric vehicles

Ramadan

Hassan

Alhelou

2022

IET Renewable Power Gen

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“…In literature, EMS has been considered in several works [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]; we can classify these strategies into two main categories:…”

Section: Introductionmentioning

confidence: 99%

“…A non-linear approach such as Passivity Based Control PBC methodology enables to guarantee the asymptotic stability of the control/system combination, another interesting approaches of energy management in hybrid electric vehicles are artificial intelligence (fuzzy and neural network), it has the necessary robustness to naturally take into account system variations, but they also require accurate sizing of the power sources with a risk of over sizing. This leads to additional costs (real and computational) and decreases system reliability which limits their real time functioning and industrial integration [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Frequency splitting approach using wavelet for energy management strategies in fuel cell ultra-capacitor hybrid system

Samia¹,

Azib²,

Kamel-Eddine³

2022

J. meas. eng.

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Using frequency splitting, two energy management strategies (EMS) based on Haar wavelet decomposition and Fourier analysis for fuel cell hybrid vehicle (FCHV) are proposed to manage efficiently the power flow between components. The paper aims to discuss the performances of the proposed EMS in terms of dynamic behavior, robustness operation, real time application and fuel economy. For apply this methodology, two EMS approaches are elaborated and successfully tested for parallel Fuel Cell/UC: conventional approach using Fourier Transform analysis (FT) and Wavelet analysis approach allowing natural frequency splitting. Finally, and to evaluate the performance and relevance of the developed approach, a comparison analysis were conducted. The simulation results exhibit the effectiveness of both strategies. Indeed, Wavelet analysis leads to better results in terms of energy flow and dynamic behavior, excellent robustness and stability of system, as well as energy economy improvement. A very relevant strategy is proposed based on Wavelet analysis using digital filtering techniques, which enables a natural frequency splitting to ensure the best global performances. In addition, the approach remains simple and suitable for real time operation.

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“…The classical CbI has been applied to the frequency stabilization of multimachine power system [12], the motion control of induction motors [13], and the temperature control of heat exchanger networks [14], whose popularity comes from its simplicity. The IDA-PBC method is applied for designing the state-feedback control laws for induction motors [15], hydroturbine systems [16], multimachine power systems considering hydroturbine with surge tank [17], a fuel cell/super-capacitor hybrid system [18], brushless DC motor [19], and electric vehicles (EVs) [20]. The popularity of the IDA-PBC method is given by its capability of injecting extra damping, and usually proper state observers are necessary for realizing practically implementable dynamic output feedback control strategies.…”

Section: Introductionmentioning

confidence: 99%

Passivity-Based Power-Level Control of Nuclear Reactors

et al. 2022

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Nonlinear power-level control of nuclear reactors can guarantee wide-range closed-loop stability that is positive for plant load-following capability. Nuclear reactor power dynamics are the tight interconnection of both neutron kinetics and thermal hydraulics, which determines that the corresponding control design model is a complex nonlinear system with large uncertainty. Although nuclear reactor dynamics are complex, it is meaningful to develop simple but effective power-level control methods for easy practical implementation and commissioning. In this paper, a passivity-based control (PBC) is proposed for nuclear reactor power-level dynamics, which has a simple form and relies on the measurement of both neutron flux and average primary coolant temperature. By constructing the Lyapunov function based on the shifted ectropies of neutron kinetics and reactor core thermal hydraulics, the sufficient condition for globally asymptotic closed-loop stability is further given. Finally, this PBC is applied to the power-level control of a nuclear heating reactor, and simulation results show the feasibility and satisfactory performance.

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Efficient experimental energy management operating for FC/battery/SC vehicles via hybrid Artificial Neural Networks-Passivity Based Control

Cited by 24 publications

References 47 publications

Robust control for techno‐economic efficient energy management of fuel cell hybrid electric vehicles

Robust control for techno‐economic efficient energy management of fuel cell hybrid electric vehicles

Frequency splitting approach using wavelet for energy management strategies in fuel cell ultra-capacitor hybrid system

Passivity-Based Power-Level Control of Nuclear Reactors

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