A comparison of rule-based and model predictive controller-based power management strategies for fuel cell/battery hybrid vehicles considering degradation

Traditional power management systems for hybrid vehicles often focus on the optimization of one particular cost factor, such as fuel consumption, under specific driving scenarios. The cost factor is usually based on the beginning-of-life performance of system components. Typically, such strategies do not account for the degradation of the different components of the system over their lifetimes. This study incorporates the effect of fuel cell and battery degradation within their cost factors and investigates the impact of different power management strategies on fuel cell/battery loads and thus on the operating cost over the vehicle's lifetime. A simple rule-based power management system was compared with a model predictive controller (MPC) based system under a connected vehicle scenario (where the future vehicle speed is known a priori within a short time horizon). The combined cost factor consists of hydrogen consumption and the degradation of both the fuel cell stack and the battery. The results show that the rule-based power management system actually performs better and achieves lower lifetime cost compared to the MPC system even though the latter contains more information about the drive cycle. This result is explained by examining the changing dynamics of the three cost factors over the vehicle's lifetime. These findings reveal that a limited knowledge of traffic information might not be as useful for the power management of certain fuel cell/battery hybrid vehicles when degradation is taken into consideration, and a simple tuned rule-based controller is adequate to minimize the lifetime cost.