Disaggregation of PHEV Energy use Under Different Energy Management Strategies

Abstract

<div class="section abstract"><div class="htmlview paragraph">Plug-in hybrid vehicles have complex energy management and are very influenced by charging behavior. Since current on-road data analysis methodologies do not take into consideration propulsion management, it is difficult to correctly estimate their energy and emissions impacts. This paper presents a methodology (ABCD Method) based only on dynamic data to assess the battery state of charge, identifying, second by second, which propulsion source is working and estimating the correspondent energy consumption, pollutant gas emissions and utility factor. Using a Portable Emission Measurement System, this methodology was developed based on real driving data obtained on four trips in two different PHEV. Excellent correlations were obtained between the estimated and measured SOC (R2>0.98). The ABCD Method uses a generic algorithm to allocate points of different propulsion combinations, correctly identifying the energy source used in over 81.9% of trip points. The ABCD method and Vehicle Specific Power (VSP) method were compared with the measurement data from the four trips, indicating that the ABDC method presents in all situations better estimates, except for HC emission, standing out in the estimate of the electric energy use (9.8% ± 6.5% vs 42.1% ± 20.8%, compared with VSP) and utility factor (5.0% ± 3.4% vs 24.7% ± 1.7%). The ABCD method is of major importance for improving the VSP methodology and the current RDE driving data analysis tools used by the European Commission since this method allows knowing which propulsion system is used at each instant.</div></div>