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Connected vehicle-based eco-driving applications have emerged as effective tools for improving energy efficiency and environmental sustainability in the transportation system. Previous research mainly focused on vehicle-level or link-level technology development and assessment using real-world field tests or traffic microsimulation models. There is still high uncertainty in understanding and predicting the impact of these connected eco-driving applications when they are implemented on a large scale. In this paper, a computationally efficient and practically feasible methodology is proposed to estimate the potential energy savings from one eco-driving application for heavy-duty trucks named Eco-Approach and Departure (EAD). The proposed methodology enables corridor-level or road network–level energy saving estimates using only road length, speed limit, and travel time at each intersection as inputs. This technique was validated using EAD performance data from traffic microsimulation models of four trucking corridors in Carson, California; the estimates of energy savings using the proposed methodology were around 1% average error. The validated models were subsequently applied to estimate potential energy savings from EAD along truck routes in Carson. The results show that the potential energy savings vary by corridor, ranging from 1% to 25% with an average of 14%.
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This content will become publicly available on January 1, 2026
Impact of flexible and bidirectional charging in medium- and heavy-duty trucks on California’s decarbonization pathway
California has committed to ambitious decarbonization targets across multiple sectors, including decarbonizing the electrical grid by 2045. In addition, the medium- and heavy-duty truck fleets are expected to see rapid electrification over the next two decades. Considering these two pathways in tandem is critical for ensuring cost optimality and reliable power system operation. In particular, we examine the potential cost savings of electrical generation infrastructure by enabling flexible charging and bidirectional charging for these trucks. We also examine costs adjacent to enabling these services, such as charger upgrades and battery degradation. We deploy a large mixed-integer decarbonization planning model to quantify the costs associated with the electric generation decarbonization pathway. Example scenarios governing truck driving and charging behaviors are implemented to reveal the sensitivity of temporal driving patterns. Our experiments show that cost savings on the order of multiple billions of dollars are possible by enabling flexible and bidirectional charging in medium- and heavy-duty trucks in California.
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- Award ID(s):
- 2152258
- PAR ID:
- 10584691
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Applied Energy
- Volume:
- 377
- Issue:
- PB
- ISSN:
- 0306-2619
- Page Range / eLocation ID:
- 124450
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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