Plug-In Hybrid Vehicle Powertrain Design Optimization: Energy Consumption and Cost

Abstract

The scope of this study is to optimize the component sizing of a fuel cell powered PHEV (PHEV-FC), using a genetic algorithm (GA) to optimize component cost for a typical urban taxi fleet usage. A simplified heuristic methodology is the first approach for the PHEV design. Cost functions for the components are estimated as well as specific power functions to perform the vehicle component sizing and cost evaluation. The used GA aims to optimize the cost of the designed vehicle and evaluate performance constrains (maximum speed and acceleration, electric range, overall performance) using an external tool, a vehicle simulator software ADVISOR, automated with the algorithm (in loop). A real measured driving cycle and official New European Driving Cycle (NEDC) are used for the vehicle simulations. Different fuel cells, motor and battery and a range of battery module number are the input data for the GA optimization regarding component selection. The initialization of the heuristic method relays on the vehicle specific power (VSP) methodology, namely on maximum power requirements of the specified driving cycle. It assumes efficiencies and main characteristics) of the components to perform an iterative calculation, followed by a trial and error evaluation. The GA is capable to tune the component sizing to the respective performance requirements. It can be seen that the cost may not have a direct relation with the consumption, since that different components lead to different vehicle weight and performance. An important limitation of the current methodology is that the vehicle optimization is fully dependent on the assigned driving cycle and performance constrains. Input data and GA parameter tuning deserves exhaustive work to achieve more precise results. The heuristic method although very fast to achieve results lacks sensitiveness regarding the proposed constraints to the design, since the evaluation process is made after the design. The GA allows adjusting better solutions to the requirements of the driving cycle and constraints, and independently selecting the fuel cell, motor and battery. Both heuristic and GA method results are compared with a conventional diesel taxi vehicle (ICEV). The designed PHEV-FC with the lowest cost and compliant with the requirements resulted from the GA method and was powered by a 24 kW fuel cell, a 130 kW motor, and a 251, 17 kWh Li-ion battery pack. Using the real Lisbon downtown driving cycle, the optimized PHEV-FC achieved a 2.1 MJ/km daily taxi service, which represents less 18 % of energy consumption than the ICEV taxi. The best results produced for the PHEV design regarding the real driving cycle have 67 % higher energy consumption and are 80 % more costly than NEDC, since NEDC it is a less demanding cycle.