The ever-growing push for reducing GHG and NOx emissions has been challenging vehicle manufacturers globally. In the USA, multi-pollutant emissions standards finalized recently by EPA, for model years 2027 and later aim to reduce the CO2 emissions by 56% and 44%, respectively, for light and medium duty vehicles by 2032. The NMOG+ and NOx are also required to be reduced by 60 – 76% by 2032 from 2026 levels. Europe is also aiming to reduce CO2 emissions by 55% by 2030 from 1990 levels and 100% by 2035.
To achieve such low levels of CO2 emissions, especially in the near-term scenario of limited EV sales, hybridization of conventional powertrains has found renewed interest. While hybrid powertrains add complexity, if optimized well for the application, they can offer best tradeoff between upfront cost, range, payload, performance, emissions and off-ambient operation. This study investigates the benefits and challenges of various hybrid architectures suitable for a pickup truck application using a model-based approach. First, a baseline vehicle model of a conventional powertrain pickup truck was developed using GT-SUITE and correlated to test data for fuel economy, and engine-out emissions over EPA regulatory cycles. Thereafter, the model was extended to represent various hybrid powertrains such as P2, P3, P1P2, P1P3 and range extender series hybrid architecture. The component sizes and energy management strategy for each hybrid architecture was then optimized using a genetic algorithm-based optimization approach to maximize fuel efficiency. The optimized hybrid powertrains were then compared against each other on performance, fuel efficiency, added curb weight, added cost and cost of ownership.