Constrained Optimization of Energy Management for a Mild-Hybrid Vehicle

Abstract : Hybrid-electric vehicles appear to be one of the most promising technologies for reducing fuel consumption and pollutant emissions. The presented work focuses on a power train architecture for mild hybrid vehicles. The complete mild-hybrid vehicle is modelled in AMESim environment and the fuel consumption for given driving cycles is estimated. The control strategies for the energy management between the two power sources are optimized with respect to fuel consumption with a classical dynamic programming (DP) method. We propose an other method based on Pontryagin Minimum Principle which furnishes results very close to the DP results for a significantly reduced calculation time. These optimization results furnish the optimal control laws from which could be derived the control laws to be implemented on the vehicle. To illustrate the potential of optimization for component design, mild hybrid vehicles with varying battery and electric motor sizes, with different types of engine (gasoline / natural gas), are evaluated in terms of consumption gain with the presented methodology.