Analytic Solutions to the Dynamic Programming sub-problem in Hybrid Vehicle Energy Management
Artikel i vetenskaplig tidskrift, 2015
The computationally demanding Dynamic Programming
(DP) algorithm is frequently used in academic research to
solve the energy management problem of an Hybrid Electric
Vehicle (HEV). This paper is focused exclusively on how the
computational demand of such a computation can be reduced.
The main idea is to use a local approximation of the gridded
cost-to-go and derive an analytic solution for the optimal torque
split decision at each point in the time and state grid. Thereby
it is not necessary to quantize the torque split and identify
the optimal decision by interpolating in the cost-to-go. Two
different approximations of the cost-to-go are considered in the
paper: i) a local linear approximation, and ii) a quadratic spline
approximation. The results indicate that computation time can be
reduced by orders of magnitude with only a slight degradation in
simulated fuel economy. Furthermore, with a spline approximated
cost-to-go it is also possible to significantly reduce the memory
storage requirements. A parallel Plug-in HEV is considered in
the paper but the method is also applicable to an HEV.
Dynamic Programming
Hybrid Electric Vehicles