Modelling and predicting energy consumption of a range extender fuel cell hybrid vehicle

Tao Zeng, Caizhi Zhang, Minghui Hu, Yan Chen, Changrong Yuan, Jingrui Chen and Anjian Zhou

Energy, 2018, vol. 165, issue PB, 187-197

Abstract: Energy consumption is an important economical index of a fuel cell hybrid vehicle (FCHV). To analyse the energy consumption of a range extender FCHV and reduce the cost of experiments, this study developed a nonlinear regression model of the powertrain of the vehicle to predict the current and voltage on the DC bus, which were used in the investigation of energy consumption, by using the intelligent algorithms including Back Propagation neural network (BP), Genetic Algorithm-Back Propagation neural network (GABP) and least square support vector machine (LSSVM). The model based on the LSSVM achieves the best predicted performance and can consider the nonlinear characteristics of the powertrain quite well. A case study was discussed by applying the obtained model and integrated with a hierarchical energy management strategy (HEMS). The specific results of energy consumption showed that it is feasible to use the predicted data of the obtained model in the analysis of the energy consumption of the FCHV.

Keywords: Range extender; Energy consumption; Intelligent algorithms; Fuel cell hybrid vehicle (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:165:y:2018:i:pb:p:187-197

DOI: 10.1016/j.energy.2018.09.086

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