The transition to low-carbon urban transport has catalyzed interest in hybrid hydrogen-electric powertrains for connected autonomous vehicles (CAVs), which offer zero tailpipe emissions, long driving range, and the potential to refuel quickly. The paper proposes a system-level optimization model for hybrid hydrogen-electric powertrains in urban traffic, enhancing vehicle energy efficiency and operational reliability by leveraging vehicle-to-vehicle connectivity and autonomous control. The suggested architecture addresses three components: real-time traffic data, vehicle-infrastructure communication, and predictive energy control, to dynamically distribute power between the fuel cell and the battery based on changing driving conditions. The simulation findings from representative urban drive cycles indicate that cumulative hydrogen consumption decreased by 0.42kg to 1.54kg per driving cycle, and average powertrain efficiency increased by 0.41 to 0.49. The optimized strategy also minimizes fuel cell power variations by 6.8 kW and reduces the battery state-of-charge variance from 0.014 to 0.006, resulting in smoother energy use and reduced component stress. In addition, the high-power acceleration events are reduced to 31 per cycle, and recoverable regenerative braking energy increases by 2.3 MJ, made possible by synchronized speed planning with CAV connectivity. Analysis of emissions shows that local exhaust gas emissions have been fully reduced and that total lifecycle energy demand has decreased by 5.6 MJ per urban cycle compared with a conventional hybrid electric powertrain under the same traffic conditions. The results overall indicate that combining hydrogen fuel cell technology with intelligent, networked, and autonomous energy management provides quantifiable improvements in efficiency, durability, and sustainability, and can be used to introduce hybrid hydrogen-electric CAVs into intelligent urban mobility systems.
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