Optimal energy management in a dual-storage fuel-cell hybrid vehicle using multi-dimensional dynamic programming

Ansarey, M; Panahi, Masoud Shariat; Ziarati, Hussein; Mahjoob, M. J.

doi:10.1016/j.jpowsour.2013.10.145

Cited by 169 publications

(67 citation statements)

References 9 publications

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“…The DP is a discrete global optimization algorithm that is widely applied to solve the problem of energy management strategy of hybrid ESS-based vehicles [11,[49][50][51][52]. In terms of the design stage of the LHD, we need to use the method of DP to obtain the optimal solution for the hybrid ESS-based optimization problem, and to evaluate the other results based on this benchmark.…”

Section: Dp-based Energy Management Strategymentioning

confidence: 99%

Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs

et al. 2017

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Abstract:Energy storage systems (ESS) play an important role in the performance of mining vehicles. A hybrid ESS combining both batteries (BTs) and supercapacitors (SCs) is one of the most promising solutions. As a case study, this paper discusses the optimal hybrid ESS sizing and energy management strategy (EMS) of 14-ton underground load-haul-dump vehicles (LHDs). Three novel contributions are added to the relevant literature. First, a multi-objective optimization is formulated regarding energy consumption and the total cost of a hybrid ESS, which are the key factors of LHDs, and a battery capacity degradation model is used. During the process, dynamic programming (DP)-based EMS is employed to obtain the optimal energy consumption and hybrid ESS power profiles. Second, a 10-year life cycle cost model of a hybrid ESS for LHDs is established to calculate the total cost, including capital cost, operating cost, and replacement cost. According to the optimization results, three solutions chosen from the Pareto front are compared comprehensively, and the optimal one is selected. Finally, the optimal and battery-only options are compared quantitatively using the same objectives, and the hybrid ESS is found to be a more economical and efficient option.

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Section: Dp-based Energy Management Strategymentioning

confidence: 99%

Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs

et al. 2017

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“…The proposed strategies can be classified into two categories: off-line optimal strategies and real-time strategies. Dynamic Programming [16] and convex optimization [9] have been used to get the off-line optimal strategy. However, the off-line optimal strategy cannot be used in real-time because it requires a priori knowledge of the driving cycle and, therefore, the design of a real-time strategy is inevitable.…”

Section: Open Accessmentioning

confidence: 99%

Power Management Optimization of an Experimental Fuel Cell/Battery/Supercapacitor Hybrid System

2015

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Abstract:In this paper, an experimental fuel cell/battery/supercapacitor hybrid system is investigated in terms of modeling and power management design and optimization. The power management strategy is designed based on the role that should be played by each component of the hybrid power source. The supercapacitor is responsible for the peak power demands. The battery assists the supercapacitor in fulfilling the transient power demand by controlling its state-of-energy, whereas the fuel cell system, with its slow dynamics, controls the state-of-charge of the battery. The parameters of the power management strategy are optimized by a genetic algorithm and Pareto front analysis in a framework of multi-objective optimization, taking into account the hydrogen consumption, the battery loading and the acceleration performance. The optimization results are validated on a test bench composed of a fuel cell system (1.2 kW, 26 V), lithium polymer battery (30 Ah, 37 V), and a supercapacitor (167 F, 48 V).

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“…The fuel cell powered hybrid drive train [12], [13] mainly contains a fuel cell system, a proton power system (PPS), an electric motor and accordingly motor control unit (MCU), a vehicle control unit (VCU), and a power converter between the fuel cell stack and the proton power system. After the accelerator, the braking pedal or other operating signals provide the power or torque command, the motor output power or torque is controlled by the VCU, as well as the energy flows between the fuel cell stack, the proton power system, and the drive train.…”

Section: Fuel Cell Vehicle Based Electric Drivesmentioning

confidence: 99%

Electric Drives in Alternative Fuel Vehicles — Some New Definitions and Methodologies

Zhang¹

2015

New Applications of Electric Drives

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This chapter focuses on some new definitions and methodologies of electric drives that are facing new challenges raised by alternative fuel vehicles. It starts with the objectives, fundamentals, and current research issues of alternative fuel vehicles based electric drives, before moving on to new definitions of unified modeling of the entire electric drive system and design of the proposed DC active power filter aimed at energy storage system chaotic current elimination. Next, novel motor control strategies taking into account alternative fuel vehicle operations are presented for improvement of sensorless drive and flux weakening control performance. Finally, conclusions of this chapter are drawn.

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Optimal energy management in a dual-storage fuel-cell hybrid vehicle using multi-dimensional dynamic programming

Cited by 169 publications

References 9 publications

Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs

Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs

Power Management Optimization of an Experimental Fuel Cell/Battery/Supercapacitor Hybrid System

Electric Drives in Alternative Fuel Vehicles — Some New Definitions and Methodologies

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