Integrated Convex Speed Planning and Energy Management for Autonomous Fuel Cell Hybrid Electric Vehicles

Fuel cell hybrid electric vehicles (FCHEVs) have zero harmful emissions, fast refueling times, and long driving ranges. Autonomous FCHEVs add benefits such as collision avoidance and driver convenience yet increase vehicle energy usage due to sensors and computation. Thus, it is important to optimize vehicle speed trajectories and the energy management strategy (EMS) of autonomous FCHEVs to minimize energy use. This article uniquely proposes to achieve this goal using convex optimization, with detailed vehicle loss calculations that can be run in real time. The two novel approaches proposed are: 1) the successive method, which solves the speed problem then the EMS problem, and 2) the integrated method, which uniquely feeds back the fuel cell efficiency to the speed algorithm to solve the problem in an iterative integrated manner. The simulation results show that the integrated method uses 0.19% to 2.37% less hydrogen than the successive method on short drive cycles with varying accessory loads, and 10.12%–21.62% less hydrogen than an arbitrary constant speed profile. On longer real-world drive cycles, the integrated method reduces hydrogen use by 1.43% to 2.82% just through speed optimization. Compared to a dynamic programming benchmark, which is not implementable in real time, the integrated method uses less than 1% more hydrogen.