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World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Articles in this Issue were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on mdpi.com as a courtesy and upon agreement with AVERE.
Open AccessArticle

Sensitivity analysis for assessing robustness of position-based predictive energy management strategy for fuel cell hybrid electric vehicle

1
Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yueong-gu, Daejeon 305-701, Republic of Korea
2
The Cho Chun Shik Graduate School of Green Transportation, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2015, 7(2), 330-341; https://doi.org/10.3390/wevj7020330
Published: 26 June 2015
Under hilly road conditions, it is difficult to achieve near-optimal performance of energy management strategy (EMS) of fuel cell hybrid electric vehicle (FCHEV). In order to achieve near-optimality, optimal state reference trajectory is predicted based on future information, and thus reference tracking controller is often considered as real-time predictive EMS. There are two approaches depending on in what way the predicted reference will be used as follows: 1) position-based predictive EMS for tracking position- dependent reference, 2) time-based predictive EMS for tracking time-dependent reference. In this paper, analytical sensitivity analysis based on Pontryagin’s minimum principle (PMP) is performed to prove robustness of position-based predictive EMS with respect to velocity uncertainty. First, optimal control problem is formulated in time and position domain, and PMP approach is used to derive boundary value problem (BVP) that achieves global optimality. Then, sensitivity differential equations are developed which describe sensitivity of original BVP with respect to velocity uncertainty. Finally, these equations will be solved simultaneously with the original BVP to compute first-order sensitivity of time- and position- dependent optimal state. Results show that sensitivity of time-dependent optimal state is much bigger than that of position-dependent optimal state because velocity uncertainty can change predicted travel time, and this effect on sensitivity is significant. Therefore, predictive EMS should use current position to track position-dependent optimal state reference in terms of the robustness with respect to velocity uncertainty.
Keywords: FCHEV (fuel cell hybrid electric vehicle); PMP (Pontryagin’s minimum principle); Position-based predictive energy management strategy; Sensitivity Analysis FCHEV (fuel cell hybrid electric vehicle); PMP (Pontryagin’s minimum principle); Position-based predictive energy management strategy; Sensitivity Analysis
MDPI and ACS Style

Han, J.; Kum, D.; Park, Y. Sensitivity analysis for assessing robustness of position-based predictive energy management strategy for fuel cell hybrid electric vehicle. World Electr. Veh. J. 2015, 7, 330-341.

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