Hybrid electric vehicles have different performance depending on power distribution and energy management. For heavy-duty vehicles, in particular, these differences will be more pronounced. This paper presents a hybrid powertrain design framework for a heavy-duty multi-purpose vehicle assuming driving conditions. A diesel-powered conventional vehicle was adopted for the hybridization target, and a series hybrid system was suggested as a suitable hybridization topology with an in-wheel motor (IWM) system. The introduced framework supplied the adequate power distribution and the IWM specification based on the speculated drive cycle and a simple energy management strategy. In particular, the reduction ratio of IWM was determined to minimize the gross mass of the motor and reduction gear. The hybridization reduced the vehicle weight by 213 kg while increasing the peak power by 53 kW. Finally, the vehicle simulation was performed using the advanced vehicle simulator for the design result from the proposed framework. The acceleration performance and gradeability limits were improved by 18 % and 10 %p, respectively, compared to the conventional vehicle. In addition, the gasoline equivalent fuel economy of the series hybrid powertrain was 53 % higher than conventional diesel powertrain for the target drive cycle.

Software tools for fuel economy simulations play an important role during design stages of advanced powertrains. However, calibration of vehicle models versus real-world driving data faces challenges owing to inherent variations in vehicle energy efficiency across different driving conditions and different vehicle owners. This work utilizes datasets of vehicles equipped with OBD/GPS loggers to validate and calibrate FASTSim (software originally developed by NREL) vehicle models. The results show that window-sticker ratings (derived from dynamometer tests) can be reasonably accurate when averaged across many trips by different vehicle owners, but successfully calibrated FASTSim models can have better fidelity. The results in this paper are shown for nine vehicle models, including the following: three battery-electric vehicles (BEVs), four plug-in hybrid electric vehicles (PHEVs), one hybrid electric vehicle (HEV), and one conventional internal combustion engine (CICE) vehicle. The calibrated vehicle models are able to successfully predict the average trip energy intensity within ±3% for an aggregate of trips across multiple vehicle owners, as opposed to within ±10% via window-sticker ratings or baseline FASTSim.

The co-adoption of distributed energy resources (DERs) – including solar photovoltaics, battery storage, and electric vehicles – offers synergistic benefits that exceed those of individual technologies. This study applies the Technology Value Mapping (TVM) framework to assess stakeholder-specific perspectives on DER co-adoption and to identify both the values of co-adoption and the barriers to broader uptake. Two workshops with participants representing consumers, regulators, developers, and utilities elicited stakeholder-identified values and perceived challenges related to DER adoption and co-adoption. Our exploratory workshops suggest that co-adoption amplifies economic, resilience, and technical value for all stakeholder groups. Widespread co-adoption is constrained, however, by affordability concerns, interoperability issues, regulatory fragmentation, and incentive misalignment. Analysis across stakeholders surfaced five systemic barrier types: information asymmetry, economic tension, regulatory complexity, infrastructure dependency, and trust deficits. These barriers frequently span stakeholder boundaries, requiring joint solutions especially between utilities and regulators. The study extends the application of TVM in this context and highlights the need for cross-sectoral strategies to scale DER co-adoption.

This study explores the circumstances when opportunity charging is economically viable in an electric transit bus network. A mixed-integer linear |

Vehicles with electrified powertrains carry the promise of significant reductions in greenhouse gas (GHG) emissions from a lifecycle analysis (LCA) standpoint compared to conventional internal combustion engine (CICE) vehicles. However, trade-offs exist between different types of electrified powertrains in terms of cost, consumer acceptance, and GHG reduction efficacy for different operating conditions. The open-source tool CarGHG was developed with an aim to enable the exploration of a plethora of parametric study scenarios, including the cost of electrification technologies, different driving patterns and charging habits, and the cost and carbon intensity of electricity and fuel blends. This paper introduces the framework of CarGHG, then showcases total cost of ownership (TCO) and LCA GHG results for select models of light-duty vehicles. Another capability of CarGHG, which is the ability to estimate the performance of “virtual” vehicle models (perceived vehicle design specifications not yet on the market), is utilized to explore future scenarios of electrification and low-carbon fuel blends for Small Sports Utility Vehicles (SUVs), a popular light-duty vehicle segment in North America. With opportunities, but also uncertainties, in future scenarios, it is likely wise to continue pursuing multiple ways towards the reduction of LCA GHG.