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Title 

Sensitivity analysis for assessing robustness of positionbased predictive energy management strategy for fuel cell hybrid electric vehicle 


Author 

Jihun Han, Dongsuk Kum, and Youngjin Park 


Conference 

EVS28, May 36, KINTEX, Korea 


Year of Pub. 

2015 



File 

EVS28_HJH_published.pdf 

Under hilly road conditions, it is difficult to achieve nearoptimal performance of energy management strategy (EMS) of fuel cell hybrid electric vehicle (FCHEV). In order to achieve nearoptimality, optimal state reference trajectory is predicted based on future information, and thus reference tracking controller is often considered as realtime predictive EMS. There are two approaches depending on in what way the predicted reference will be used as follows: 1) positionbased predictive EMS for tracking positiondependent reference, 2) timebased predictive EMS for tracking timedependent reference. In this paper, analytical sensitivity analysis based on Pontryagin¡¯s minimum principle (PMP) is performed to prove robustness of positionbased 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 firstorder sensitivity of time and positiondependent optimal state. Results show that sensitivity of timedependent optimal state is much bigger than that of positiondependent 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 positiondependent optimal state reference in terms of the robustness with respect to velocity uncertainty.








