GRAB-ECO for Minimal Fuel Consumption Estimation of Parallel Hybrid Electric Vehicles

This is an O Abstract — As a promising solution to the reduction of fuel consumption and CO2 emissions in road transport sector, hybrid electric powertrains are confronted with complex control techniques for the evaluation of the minimal fuel consumption, particularly the excessively long computation time of the design-parameter optimization in the powertrain’s early design stage. In this work, a novel and simple GRaphical-Analysis-Based method of fuel Energy Consumption Optimization (GRAB-ECO) is developed to estimate the minimal fuel consumption for parallel hybrid electric powertrains in lightand heavy-duty application. Based on the power ratio between powertrain’s power demand and the most efficient engine power, GRAB-ECO maximizes the average operating efficiency of the internal combustion engine by shifting operating points to themost efficient conditions, or by eliminating the engine operation frompoorly efficient operating points to pure electric vehicle operation.A turningpoint is found tomeet the requirement of thefinal state of energyof thebattery,which is charge-sustainingmode in this study. TheGRAB-ECOwas testedwithboth lightandheavy-dutyparallel hybrid electric vehicles, andvalidated in termsof theminimal fuel consumption and the computation time. Results show that GRAB-ECO accurately approximates the minimal fuel consumptionwith less than 6%of errors for both lightandheavy-duty parallel hybrid electric powertrains. Meanwhile, GRAB-ECO reduces computation time by orders of magnitude compared with PMP-based (Pontryagin’s Minimum Principle) approaches.