Model-Based Evaluation of Hybrid Powertrains for a Light Duty Pickup Truck Application FEV North America Incorporated

Format:

Book

Conference/Event

Author/Creator:

Fnu, Dhanraj, author.

Contributor:

Correia Garcia, Bruno

Franke, Michael

Joshi, Satyum

Paul, Sumit

Conference Name:

WCX SAE World Congress Experience (2025-04-08 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2025

Summary:

In recent years, the stronger push for reducing GHG and NOx emissions has challenged vehicle manufacturers globally. In USA, Multi-Pollutant Emissions Standards for Model Years 2027 and Later Light Duty and Medium-Duty Vehicles released by EPA in April 2023 aims to reduce the CO2 emissions by 56% and 44%, respectively, for light and medium duty vehicles by 2032 from 2026 levels. It also includes the NMOG+ NOx standards, which require a 60 76% reduction by 2032 from 2026 levels for light to medium-duty vehicles. Europe also aims 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 electrified powertrains such as P2, P3, P1P2, P1P3, range extender and Battery Electric Vehicle (BEV) 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 powertrains were finally compared against each other on performance, fuel efficiency, added curb weight, added cost and cost of ownership.In comparison to the baseline vehicle, the optimized P1P2 and P1P3 parallel hybrid configurations showed a 29% and 32% increase in fuel economy over the regulatory cycles in charge sustaining mode, respectively. The range extender concept (referred to as hybrid BEV architecture in the study) with a dedicated hybrid engine showed the highest potential of 46% increase in fuel economy along with 75% reduction in engine-out NOx emissions. The hybrid BEV architecture also showed the lowest Total Cost of Ownership (TCO) among the other electrified powertrains

Notes:

Vendor supplied data

Publisher Number:

2025-01-8532

Access Restriction:

Restricted for use by site license