Performance assessment of a predictive pre-heating strategy for a hybrid electric vehicle equipped with an electrically heated catalyst

Abstract

• A 0-D model of a Diesel PHEV with state-of-the-art EATS has been developed. • An EHC pre-heating strategy is developed to meet the EURO7 worst case scenario. • Reduction of cold-start tailpipe NO x emissions is achieved using navigation data. • EATS manufacturing cost can be reduced still complying with the regulations. In recent years, hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations on CO 2 emission. However, reduced engine load and repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned. For this purpose, a representative 0-D model has been considered to define the most convenient pre-heating strategy and different real driving scenarios have been simulated to test the proposed EHC predictive control strategy. Although the pre-heating introduction implies an additional energy request which results in increased fuel consumption, the results show that the final NO x emission over a complete driving cycle can be reduced up to more than 60% compared to the base EHC strategy. Moreover, this would allow to comply with the scenarios introduced by the Euro 7 regulation proposal, while enabling the adoption of a simplified EATS architecture resulting in reduced manufacturing costs.