Soroush Roghani

Decarbonizing the transportation sector requires practical pathways for reducing fossil-fuel consumption and greenhouse gas emissions from existing rail systems. Although railway electrification through catenary systems offers an effective pathway toward low-emission rail transportation, its widespread implementation on existing non-electrified corridors can be constrained by substantial capital costs, infrastructure modifications, and deployment complexity. Battery-electric and battery-supported locomotive technologies provide an alternative pathway for rail decarbonization by enabling progressive fleet electrification while reducing dependence on extensive wayside electrical infrastructure. This study presents a route-level energy assessment to determine the onboard battery energy storage system (BESS) capacity required to retrofit an F59PH diesel passenger locomotive for battery-electric operation on the Piedmont corridor. The journey is simulated using the Single Train Simulator (STS), incorporating route characteristics, speed restrictions, station stops, and vehicle configuration. The resulting traction-energy demand provides the basis for evaluating commercially available battery technologies under battery-only and hybrid battery-supported operating scenarios. The simulation indicates a route-level energy consumption of 25.2 kWh/km. Among the evaluated battery technologies, the configuration requiring the fewest packs for baseline battery-only operation consisted of 142 packs, sufficient to satisfy the total route energy demand. Incorporating the added battery mass into the vehicle-energy model modestly increased this requirement to 146 packs. Under the hybrid battery-supported scenario, approximately 1305 kWh of regenerative braking energy was recoverable, with the lowest-pack-count configuration (Type D) providing sufficient capacity to enable nearly 40 min of battery-only operation. These results demonstrate how onboard energy storage and regenerative braking can support incremental rail decarbonization by reducing diesel operation, recovering otherwise dissipated braking energy, and potentially lowering the infrastructure burden associated with conventional corridor-wide electrification. As a route-level case study, the proposed methodology provides a transferable framework for evaluating onboard battery integration, identifying appropriate battery capacity, and supporting decarbonization strategies across passenger, light-rail, and heavy-rail applications.

Lithium-ion battery (LIB)-powered locomotives have emerged as a promising alternative to conventional rail electrification by reducing dependence on overhead catenary systems, lowering infrastructure costs, and improving operational flexibility. However, train failures involving power loss or mechanical faults present significant challenges for battery-powered rail systems, particularly on single-track corridors where alternate route options are limited. Consequently, the implementation of a reliable limp-home strategy is more complex than in road electric vehicles (EVs), requiring consideration of battery availability, rescue logistics, and track accessibility. This study investigates limp-home operation and rescue planning for a battery-powered historic trolley operating on a 20 km heritage route in North Carolina. The trolley is powered by a dedicated LIB trailer and supported by battery-charging (BC) infrastructure based on inductive power transfer (IPT) technology. A comprehensive framework is developed that integrates time–space analysis, cellular automata (CA)-based failure-risk modeling, and battery-energy assessment to evaluate train-failure scenarios and recovery strategies. The results identify critical failure regions along the route and demonstrate the benefits of strategically deploying additional LIB rescue trailers and wireless power transfer (WPT) infrastructure. A revised rescue strategy incorporating two additional LIB trailers, together with static and dynamic WPT systems, substantially reduces recovery time and improves the likelihood of maintaining scheduled excursions. Emergency energy analysis further shows that WPT-assisted operation can significantly extend limp-home capability under low state-of-charge conditions. Based on the integrated analysis, a tiered limp-home decision framework is developed to support operator decision-making during train failures. The proposed methodology provides a practical approach for enhancing the resilience, recoverability, and operational reliability of battery-powered heritage rail systems and can serve as a foundation for future battery-electric rail applications.

Lithium-ion battery (LIB) wireless charging using inductive power transfer (IPT) represents a transformative pathway for transportation electrification. While applications in railway systems remain limited, early studies highlight significant promises for implementation. This paper presents a hybrid energy-supply framework integrating LIB, inductive battery charging (BC) charging, and battery swapping (BS) to support a 20 km heritage trolley excursion between Belmont and Gastonia, NC. A kinematic simulation was developed to estimate traction energy demand, yielding 56 kWh per trip, or 112 kWh for two daily round trips. Finite element analysis (FEA) was conducted to design an LCL-s compensated 3 kW IPT system. Two transmitter configurations were evaluated: W–I ferrite cores (peak coupling ~0.22) and magnetic concrete slabs (~0.20). Although ferrite offers higher efficiency, magnetic concrete demonstrates superior durability and integration potential. Simulation results indicate that wireless charging alone, whether static or dynamic, is insufficient; similarly, a single daily BS strategy provides only 96 kWh. Seven BC-BS hybridization scenarios were evaluated, showing that mid-day swaps combined with either static or dynamic IPT produce a 12–16 kWh surplus. The most practical approach is a one-pack swap supplemented by uniformly distributed static pads, providing energy neutrality. This hybrid pathway ensures operational sufficiency, structural resilience, and compatibility with heritage rail preservation.

Despite the commercial success of lithium-ion batteries (LIBs), the risk of thermal runaway, which can lead to dangerous fires, has become more concerning as LIB usage increases. Research has focused on understanding the causes of thermal runaway and how to prevent or detect it. Additionally, novel thermal runaway-resistant materials are being researched, as are different methods of constructing LIBs that better isolate thermal runaway and prevent it from propagating. However, field firefighters are using hundreds of thousands of liters of water to control large runaway thermal emergencies, highlighting the need to merge research with practical observations. To study battery fire, this study utilized a temperature abuse method to increase LIB temperature and investigated whether thermal runaway can be suppressed by applying external cooling during heating. The batteries used were pouch-type ones and subjected to high states of charge (SOC), which primed the thermal runaway during battery temperature increase. A water spray method was then devised and tested to reduce battery temperature. Results showed that, without cooling, a thermal runaway fire occurred every time during the thermal abuse. However, external cooling successfully prevented thermal runaway. This observation shows that using water as a temperature reducer is more effective than using it as a fire suppressant, which can substantially improve battery performance and increase public safety.

The surge in lithium-ion battery (LIB) use, essential for mass-scale renewable energy storage, raises concerns about fire hazards. However, to date, there is a lack of industry-wide understanding of large-scale LIB fire propagation. This paper suggests a translational forensic approach to promote fire safety awareness and introduces the cellular automata (CA) model coupled with the Monte Carlo (MC) approach to address the complex fire propagation simulation within an energy storage system (ESS). The objective is to demonstrate that the CA-MC model can provide a flexible and scalable connection for all levels of battery fire studies. The numerical model is coupled with experimental tests which have been performed to establish the actual timing of fire propagation from a single source. Cellular automata simulation, conducted through hybrid modeling and an applied risk analysis approach to evaluate fire hazards associated with LIBs, offers crucial insights into potential risks. The results demonstrate that, with fire incident initiation at a probability of 0.1 (10%), 33% of batteries will burn, and at a probability of 0.6 (60%) and beyond, the entire battery module will face complete burndown. Achieving full combustion of the entire module will take only approximately 42 timesteps on average, indicating rapid fire propagation. The actual time for a complete fire to occur in the battery module has been estimated to be 304 s per timestep, or 3.5 h total. Using this example, it is shown that the CA-MC approach can be extended to many other aspects of battery fire studies and is ideal as a translational tool, spanning all domains of the LIB industry.