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Aging-Aware Optimal Energy Management Control for a Parallel Hybrid Vehicle Based on Electrochemical-Degradation Dynamics

IEEE Transactions on Vehicular Technology
2020

Hybrid electric vehicles offer the best alternative to gasoline-only powered vehicles as they combine a conventional propulsion system with an electric propulsion system. A supervi8 sory controller is needed to optimally manage the energy on-board. Published works on this topic have mainly focused on strategies aimed at minimizing the fuel consumption. In this article, we address the problem of designing a supervisory controller that achieves minimum fuel consumption while optimally preserving battery life. Electrochemical degradation dynamics are used in the multi-objective problem formulation to accurately capture, and control battery performance, and aging during the control design phase. The electrochemical degradation model accounts for the electrolyte dynamics to capture high C-rate operation of the battery which are properl in charge sustaining hybrid powertrains. We resort to the optimal control formalism, and nonlinear optimization techniques along with the full discretization approach (in the state, and in the control) to cast the energy management problem into a large scale non-linear programming problem, that is able to deal with multi-scale dynamics, namely from the stiff electrolyte battery dynamics to map-based slow dynamics of the actuators. Numerical simulations conducted over four different standard driving cycles (with, and without road grades) show that our aging-aware energy management approach is able to significantly reduce the deteri28 oration of the battery, while retaining very good fuel reduction performance.