Hierarchical Energy Optimization Strategy and Its Integrated Reliable Battery Fault Management for Hybrid Hydraulic-Electric Vehicle

Reduction of fuel consumption is an indispensable part of automotive industry in recent years. This induces several developments of hybrid vehicles with different structures. This paper deals with reliable and robust energy management strategy for a hybrid hydraulic-electric intelligent vehicle. The main objective of this paper is the development of a suboptimal control strategy based on fuzzy logic and neural network for minimizing total energy consumption while ensuring a better battery life. For this purpose, fuzzy supervisory fault management, which can detect and compensate the battery faults, regulates all of the possible vehicle's operation modes. Then, control strategy based on fuzzy logic controller (FLC) is developed. The FLC membership function parameters are tuned by employing neural network to manage power distribution between electric motor and internal combustion engine (ICE). Control strategy is switched between optimized FLCs to enhance the suboptimal power split between the different energy sources and manage the ICE to work always in the vicinity of its optimal condition. Finally, a robust fuzzy tuning controllers are investigated to give a good torque set point tracking. Simulation results, while using TruckMaker/MATLAB software, confirm that the proposed approach leads to suboptimal energy consumption of the vehicle for any unknown driving cycles and compensate battery faults effects.