燃料电池汽车车速与能量联合优化

With the rapid development of new technologies such as the internet of things, cloud computing, and big data, vehicle energy optimization from the perspective of traffic behavior and road network systems has ushered in new opportunities. Aiming at the scene of fuel cell vehicles passing through multiple signal lights, a co-optimization method of vehicle speed and energy based on a static hydrogen consumption map is proposed. Combined with the powertrain structure of the fuel cell vehicle, the hydrogen consumption of the vehicle is calculated offline by dynamic programming(DP), and the static hydrogen consumption map of the vehicle at different speeds and accelerations is obtained. Based on the static hydrogen consumption map and traffic signal timing information, an optimal vehicle speed trajectory is generated with the help of the DP algorithm. The alternating direction method of multipliers(ADMM) is used to solve the energy management problem, and a cyclic constraint inspection strategy is used to constrain the fuel cell system power change rate. The simulation results show that the co-optimization calculation of the vehicle's optimal speed trajectory and energy management has real-time potential. The optimization result of this method is only about 1% difference from the optimal energy-saving performance of DP offline calculation, and it is more than 17% higher than the hydrogen saving of the improved intelligent driving model(IDM) under the energy management strategy based on ADMM.