Multi-Objective Optimization of the Fuel Cell Hybrid Electric Powertrain for a Class 8 Heavy-Duty Truck

To decarbonize heavy-duty vehicles solely through electrification with batteries is challenging as large batteries are required for a meaningful range, severely impacting payload. Employment of hybrid electric powertrains where fuel cells are integrated with batteries can deliver increased range and payload. However, the energy balance between the fuel cell and the battery needs to be analyzed to optimize the sizing of the powertrain components. This study has performed a multi-objective optimization using genetic algorithm to obtain the optimum range and hydrogen consumption for a DAF 44 tons heavy-duty truck. The proposed truck powertrain has been numerically modelled in AVL CRUISE M software. The electric drive from Involution Technologies Ltd and Bramble Energy Ltd’s printed circuit board fuel cell (PCBFC) are used in the model. The model considers the main powertrain control system variables, and the optimization is performed using AVL real road driving cycle, which is based on high altitude climb for a truck with average power requirement of the motors of 300 kW. From the results of the optimization, five design points were recommended in pareto domain, and the transient results were plotted for these operating points to decide the optimum scenario. At the selected design point the size of the H2 storage tank, fuel cell and battery packs equals to 65 kg H2 on-board storage, 270 kW fuel cell and 257 kWh respectively. The proposed fuel cell truck running the highly demanding AVL drive cycle has a 570 km range, compared with 211 km range for battery-electric only (with battery total capacity of 516.16 kWh) and hydrogen consumption of 12.46 kg/100km at fully laden payload (44 tons).