Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

The next generation of the Volt vehicle with the new “Voltec” extended-range propulsion system was introduced into the market in 2016. The second-generation Volt’s powertrain architecture provides five modes of operation, including two electric vehicle operations and three extended-range operations. Vehicle testing was performed on a chassis dynamometer set within a thermal chamber at the Advanced Powertrain Research Facility at Argonne National Laboratory. The study first focused on assessing the improvement of the new Voltec system by comparing the system efficiency with the previous system. Second, control behavior and performance were analyzed under normal ambient temperature to understand the supervisory control strategy on the Voltec system based on the test data. The analysis focused on the engine on/off strategy, powertrain operation mode, energy management, and engine operating conditions. Third, test data from the control analysis were used to summarize the vehicle control logic.

This article presents an experimental validation of energy savings achieved through cooperative driving automation (CDA) measured by vehicle-in-the-loop (VIL) testing in car-following scenarios. The impacts of different CDA classes—from status sharing to prescriptive—on vehicle energy efficiency are explored. In the experiments, a plug-in hybrid electric vehicle runs on a chassis dynamometer integrated with simulation software that creates a virtual environment. Results indicate that when agreement-seeking cooperation operates with even a minimal number of vehicles, energy can be saved by up to 5% over human driving. Our findings highlight the considerable promise of CDA technologies for enhancing energy efficiency, especially fostering research on agreement-seeking cooperation.