4.4 Article

The impact of hybridization, engine combustion method, and energy management system connectivity on heavy-duty vehicle operation

Publisher

SAGE PUBLICATIONS LTD
DOI: 10.1177/0954407020983048

Keywords

Vehicle energy management; connected vehicles; hybrid electric vehicles; power production

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A wide range of strategies for reducing energy consumption from heavy-duty vehicles have been explored in this study, including vehicle electrification and real-time energy management. It was found that altering combustion strategies can improve fuel efficiency under different hybridization levels and engine combustion modes. Connectivity in vehicles also plays a role in energy management, with real-time optimization of energy production contributing to improvements in fuel efficiency.
A wide range of strategies for reducing energy consumption from heavy-duty vehicles have been explored from vehicle electrification to real-time vehicle energy management based on vehicle-to-vehicle and vehicle-to-infrastructure communication. Full electrification of heavy-duty vehicles can be challenging due to current limitations on battery energy density. However, hybridization and the implementation of high efficiency engines present other potential near-term solutions. In contrast to many prior studies that have explored the use of one or two of these techniques, this work discusses the combined influence of hybridization level, engine combustion mode, and connected energy management on fuel efficiency in heavy-duty applications. The impact of hybridization in different driving conditions is quantified and the effectiveness of hybrid powertrain structures with different engine combustion strategies is also explored. Utilizing an alternative combustion strategy can improve fuel efficiency by 5% in conventional and mild hybrids but was found to have a more minimal impact in full hybrids. An additional layer of complexity is also introduced when vehicles have some degree of connectivity and this influence on the energy management method is investigated by comparing control approaches which leverage current and future vehicle speed information. Connectivity and the ability to optimize energy production in real-time was found to be essential in uncertain cases and enable improvements in fuel consumption of up to 12% over baseline cases.

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