Hydrogen technologies are among the main candidates to reduce carbon emissions in the automotive transport sector. Among the innovative solutions, Electric Vehicles (EVs) featuring hybrid powertrains, combining battery packs and hydrogen Fuel Cell (FC) stacks, are gaining prominence in our pursuit of sustainability objectives.
Nonetheless, realizing the full potential of these hybrid vehicles hinges on the implementation of efficient Energy Management Strategies (EMS). In this study, we present an integrated EMS approach to achieve extended driving ranges and reduced energy consumption. This is achieved primarily by operating the FC within its high-efficiency range, while ensuring that the battery packs operate in a charge-sustaining mode. The EMS is crafted through an adaptive algorithm that takes into account various driving conditions to establish the most suitable sub-optimal control strategy.
An integrated offline algorithm is developed: starting from an extensive sample of driving cycles, it is able to generate a set of sub-optimal fuzzy controllers, to be directly implemented onboard. These controllers are thoughtfully designed to replicate the optimal choices obtained through Dynamic Programming applied to the most representative driving cycles, as identified by the K-Means clustering algorithm.
Subsequently, a Driving Pattern Recognition (DPR) technique has been implemented on the vehicle model. This technique empowers real-time detection of the current driving conditions and facilitates seamless adaptive switching between the appropriate controllers.
Analysis has been performed for a microcar application, including an FC stack validated by experimental tests. The results have been evaluated for hydrogen fully discharge random missions and ambient temperature of 25 ° C, covering about 100km, with an increase of up to 9% compared to a range extender strategy. The improved performance (about 7% greater driving range) with respect to the range extender strategy has also been conserved for a more demanding driving cycle where additional security features have been added to the developed EMS to preserve the SOC to drop below 68%. Furthermore, the effectiveness of the proposed strategy is demonstrated by the increase in the mean efficiency of the fuel cell stack compared to the range extender strategy, approximately 10%.