Advanced Energy and Thermal Management Control Strategy for Heavy-Duty Fuel Cell Powertrains

<div>Medium- and heavy-duty fuel cell electric vehicles (FCEV) have gained attention over the battery electric vehicles, offering long vehicle range, fast refueling times, and high payload capacity. However, FCEVs face challenges of high upfront system cost and fuel cell system durability. To address the cost sensitivity of the fuel cell powertrain, it is imperative to maximize the operating efficiency of the energy and thermal management system while meeting the fuel cell durability requirements. This article presents an advanced adaptive control strategy for each of the energy and thermal management systems of a FCEV to maximize operating efficiency as well as vehicle performance.</div> <div>The proposed adaptive energy management strategy builds upon a real-time equivalent consumption minimization strategy (ECMS), which is updated based on a horizon prediction algorithm using GPS and navigation data of the route. The algorithm predicts the battery state of charge (SOC) for a defined horizon, which is used to predict the target SOC for the real-time ECMS strategy to minimize hydrogen consumption. For a long-haul heavy-duty truck application, the proposed adaptive ECMS strategy showed 1.8% and 1% improvements in fuel efficiency when compared to rule-based and baseline ECMS strategies through model-in-loop (MiL) evaluation.</div> <div>In addition, this article presents an adaptive thermal management strategy that integrates predictive and real-time control approaches, such as the adaptive ECMS. The predictive control strategy leverages GPS and navigation data to forecast component temperatures over a predefined horizon prediction. The predicted component temperatures are then utilized to adjust the target component temperatures for the real-time linear quadratic regulator (LQR) control algorithm. LQR is deployed to minimize the energy consumption of the thermal management system while ensuring that component temperatures are maintained within limits during aggressive duty cycles. Lastly, MiL evaluations were conducted on a validated plant model to verify the developed adaptive thermal management control strategy.</div>