Abstract
This paper presents a comprehensive optimization procedure of a series electric hydraulic hybrid vehicle powertrain and control through the interactive adaptive-weight genetic algorithm method. The optimization simultaneously maximizes the driving range and battery lifespan, while minimizing onboard energy storage system mass. In this context, the design variables of the overall hydraulic drivetrain and the electric system were optimized. Moreover, a fuzzy-logic controller, which outputs the electric motor start-stop state and the torque applied to the pump which pressurizes the accumulator, is likewise considered in the formulation of the optimization problem to tune its membership functions, rules and weights. To ensure robust solutions, the electric–hydraulic vehicle was optimized under a combination of three standard driving cycles, which have antagonistic characteristics. Among the obtained optimum solutions, two configurations stood out with the driving range of 167.95 km and 199.73 km when using a battery of 320.23 kg and 384.12 kg and obtaining a battery life cycle of 53177 h and 46531 h, respectively. Moreover, these solutions were also tested under four different real-world driving cycles to evaluate their autonomy and performance, reaching driving ranges from 147 km in highway scenarios to over 262 km in urban cycles. The optimum configurations were compared with an also optimum electric vehicle powered by a battery-ultracapacitor hybrid energy storage system, obtaining a reduction of up to 9.57% in the ratio between powertrain cost and driving range. Finally, the optimization results indicate that electric hydraulic hybrid vehicle powertrain architectures can be a very attractive propulsion technology regarding both sustainable and economical aspects, effectively reducing battery aging by the use of a high power density hydraulic accumulator, which acts as a peak power buffer unit.
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