Economic Viability Study of an On-Road Wireless Charging System with a Generic Driving Range Estimation Method

In order to promote the driving range of the electric vehicles (EVs), decrease the demand for large capacity battery and create more charging opportunities for the EVs, the static-dynamic hybrid wireless charging system is presented to utilize waiting time of traffic lights at intersections to replenish electricity in this paper. Firstly, the topology and principle of the proposed static-dynamic hybrid wireless charging system with short-segmented coils at traffic lights are introduced. Secondly, the general circuit model of the static-dynamic hybrid wireless charging system with multi-coupling between the primary and secondary sides is developed. The design method of the compensation circuit in primary side based on the number and the positions of the energized primary coils is investigated. After analyzing the characteristics of the system varying with the position of the single load, the control conceptions of the energizing mode alternating in primary side and the combination of the primary compensation capacitors are put forward. Then the power stabilization control strategy of the static-dynamic hybrid wireless charging system with multi short-segmented coils and multi loads is proposed. Finally, the theoretical analyses are verified with the experiments.

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Remaining Driving Range Estimation for Electric Vehicles through Information Fusion Method

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.668-669.641 ◽

2014 ◽

Vol 668-669 ◽

pp. 641-646

Author(s):

Guang Ming Liu ◽

Hong Fu ◽

Lan Guang Lu ◽

Yan Jing Wang ◽

Jian Feng Hua ◽

...

Keyword(s):

Electric Vehicle ◽

Information Fusion ◽

Estimation Error ◽

Estimation Method ◽

Test System ◽

Range Estimation ◽

Environmental Friendliness ◽

Range Anxiety ◽

Driving Range ◽

Driving Conditions

Electric vehicle (EV) is one of the current research focuses due to its environmental friendliness, but the inaccuracy in remaining driving range (RDR) estimation lowers the consumers’ confidence on EVs. This paper introduces a remaining driving range estimation method based on information fusion (RDRIF), in which the RDR is determined by the fusion of the calculated range (calculation of the present battery and vehicle consumption states) and the cumulated range (cumulation of the real-traveled distance) to provide a accuracy RDR result. The RDRIF algorithm was embedded in a type of pure electric vehicle, and a set of vehicle experiments was carried out on a dynamometer test system. Two urban driving cycles representing normal and aggressive driving conditions are implemented in the tests to validate the effectiveness of RDRIF. The results show that the RDRIF could provide a stable and convergent estimation result under both driving conditions compared with the traditional methods, and the estimation error could be rapidly limited to ±5%, which effectively reduces the passengers’ range anxiety.

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