Electric Vehicles

Navigating the Gig Economy: Transportation Labor Challenges Facing California’s App-based Ridehailing and Courier Drivers

Susan Shaheen
Wolfe, Brooke
Cohen, Adam
2026

Given the dynamic landscape surrounding the classification of workers in California, it is important to consider how the existing legal and regulatory environment may impact app-based gig drivers, including transportation network companies (TNCs, also known as ridehailing) and courier network services (CNS). Using a multi-method approach, we conducted a literature review (n = 41 sources), expert interviews (n = 8), and case study analysis (n = 7) between October 2022 to May 2024 to better understand how California’s gig drivers are impacted by state legislation and regulation (i.e.,...

Electrifying Long-haul Freight Trucks Reduces Societal Costs in the United States

Porzio, Jason
McNeil, Wilson
Tong, Fan
Scott Moura
Auffhammer, Maximilian
Scown, Corinne D.
2026

Abstract Electrifying long-haul heavy-duty vehicles (HDVs) entails high private costs but offers substantial reductions in external costs by substituting diesel combustion with electricity generation. We combine technoeconomic analysis and life-cycle assessment of lithium-ion battery electric (BE) and diesel HDVs to estimate total private costs and monetized climate and health damages in the United States. In 2025, BE-HDVs are estimated to have 46% higher private costs ($0.71 mile⁻¹) than diesel trucks, decreasing to 33% ($0.52 mile⁻¹) by 2035. However, their external costs are 64–69%...

Macroscopic Modeling and Hierarchical Control of Battery Swapping Stations

Wang, Ruiting
Čičić, Mladen
Scott Moura
Maria Laura Delle Monache
2025

Battery swapping offers a compelling alternative to fast charging for large EV fleets. By decoupling charging from vehicle dwell time, battery swapping stations (BSS) can charge batteries slower, reducing grid strain and extending battery life, while enabling quick vehicle turnaround. In this work, we present a hierarchical control architecture for large-scale BSS that addresses the computational limits of conventional integer programming approaches. By adopting a macroscopic model that represents battery states as a continuous distribution, our method captures nonlinear battery dynamics...

Energy Efficient Nonlinear Microscopic Dynamical Model for Autonomous and Electric Vehicles

Yeo, Yuneil
Lee, Jaewoong
Scott Moura
Maria Laura Delle Monache
2025

This article proposes a nonlinear microscopic dynamical model for autonomous electric vehicles (A-EVs) that considers battery energy efficiency in the car-following dynamics. The model builds upon the Optimal Velocity Model (OVM), with the control term based on the battery dynamics to enable thermally optimal and energy-efficient driving. We rigorously prove that the proposed model achieves lower energy consumption compared to the Optimal Velocity Follow-the-Leader (OVFL) model. Through numerical simulations, we validate the analytical results on the energy efficiency. We additionally...

Integrating Flight and Charging Schedules in Urban Air Mobility

Cao, Shangqing
Jiang, Xuan
Bulusu, Vishwanath
Chakrabarty, Anjan
Mark Hansen
Onat, Emin
Raja Sengupta
Zou, Bo
2024

This paper investigates the simultaneous optimization of flight schedule and charging policy of electric vertical takeoff and landing aircraft for Urban Air Mobility operations. An optimization model is developed for a two-vertiport system to design an efficient flight schedule, including re-balancing flights, and a charging policy that serves a given demand with the objective of minimizing the required fleet size. The results highlight that charging aircraft to a lower State of Charge level during peak demand periods and to a higher level during off-peak times effectively reduces the...

eVTOL Fleet Selection Method for Vertiport Networks

Jasenka Rakas
Jeung, Jeffery
So, Duston
Ambrose, Paul
Chupina, Valeria
2021

To date, there have been over 400 electric Vertical Takeoff and Landing (eVTOL) air vehicle designs that vary significantly in terms of design concepts, thrust type, air vehicle size or passenger seating capacity. Our study proposes a method for exploring ranking of passenger eVTOLs for vertiport network routes within large metropolitan regions. The method uses a benchmarking approach to indicate the eVTOLs most suitable to perform in the determined operational envelope. The study includes (i) a database, which was developed from open-source data that contains declared eVTOL performance...

Robust Estimation of State of Charge in Lithium Iron Phosphate Cells Enabled by Online Parameter Estimation and Deep Neural Networks

Shi, Junzhe
Kato, Dylan
Jiang, Shida
Dangwal, Chitra
Scott Moura
2023

This paper addresses the state of charge estimation problem in lithium iron phosphate (LFP) battery cells. LFP cells are particularly challenging because their fat open circuit voltage (OCV) curve means OCV-based battery models are weakly observable. This means standard methods for SOC estimation don't easily converge to the true SOC. Additionally, in practice, estimates must be accurate in the face of biased noise on current input, as well as mean-zero noise on measurements. As such, we aim to create an estimator that is accurate when facing these types of noise. We accomplish this with a...

Distributionally Robust and Data-Driven Solutions to Commercial Vehicle Routing Problems

Keyantuo, Patrick
Wang, Ruiting
Zeng, Teng
Vishwanath, Aashrith
Borhan, Hoseinali
Scott Moura
2023

In this paper, we study the routing of commercial electric trucks through an application of distributionally robust optimization (DRO) for route planning and dispatch. This approach aims to minimize total cost of operation for the fleet, and considers the variability in energy consumption due to uncertain road conditions, traffic, weather and driving behavior. Furthermore, we augment the distributionally robust energy minimizing vehicle routing problem by learning the energy efficiency distribution over a horizon. We show that convergence to the true distribution is achieved while learning...

Advancing Alternative Fuel Aviation Technologies in California

Liu, Yati
Mark Hansen
Ro, Jin Wook
Murphy, Colin W.
2025

The aviation sector in California is facing increased pressure to reduce its carbon footprint, leading to a growing interest in alternative fuel aviation (AFA) technologies such as sustainable aviation fuel (SAF), as well as electric- and hydrogen- powered aircraft. The report develops a California Aviation Energy Model (CAVEM), examining various AFA technologies and analyzing possible policy options. The analysis emphasizes the importance of SAF in the short term, with projections indicating sufficient supply for intrastate flights and capped vegetable oil-based fuel consumption. Long-...

Integrating Urban Air Mobility into the Power Grid through Smart Charging Solutions

Wu, Jiaman
Cao, Shangqing
Mark Hansen
Marta Gonzalez
2025

Adapting the existing power grid to support large-scale urban air mobility (UAM) operations using electric vertical take-off and landing (eVTOL) aircraft presents a critical infrastructural challenge that needs to be tackled. To this end, this paper presents a framework for estimating the potential of smart charging to improve power system welfare when integrating large-scale UAM into the power grid. We first estimate passenger travel demand for UAM from location-based service (LBS) data. Then we obtain the feasible charging window of aircraft by solving a fleet dispatching problem to...