Related papers: Round-Trip Energy Efficiency and Energy-Efficiency…
Flexible loads, especially heating, ventilation, and air-conditioning (HVAC) systems can be used to provide a battery-like service to the power grid by varying their demand up and down over a baseline. Recent work has reported that…
The goal of this project is to determine the feasibility of calculating a travel route for an electric vehicle (EV) that will require the least amount of energy for the trip, and thus extending the range of the EV. To achieve this goal, the…
This paper presents a novel probabilistic data-driven approach to trip-level energy consumption estimation of battery electric vehicles (BEVs). As there are very few electric vehicle (EV) charging stations, EV trip energy consumption…
This paper investigates the effect of the powertrain efficiency map on energy optimal speed trajectories, especially stop-to-stop trajectories. A variety of different efficiency maps are explored and the energy optimization process is…
The latest advancements and near-future trends in automotive battery packs, underlying regulatory compliance, and performance requirements are presented in this paper. In response to these specifications, high-level solutions that converge…
The rapid adoption of electric vehicles (EVs) in modern transport systems has made energy-aware routing a critical task in their successful integration, especially within large-scale transport networks. In cases where an EV's remaining…
We study the problem of eco-routing for Plug-In Hybrid Electric Vehicles (PHEVs) to minimize the overall energy consumption cost. We propose an algorithm which can simultaneously calculate an energy-optimal route (eco-route) for a PHEV and…
An electric car equipped with a battery of a finite capacity travels on a road network with an infrastructure of charging stations. Each charging station has a possibly different cost per unit of energy. Traversing a given road segment…
Supercapacitors are increasingly used as energy storage elements. Unlike batteries, their state of charge has a considerable influence on their voltage in normal operation, allowing them to work from zero to their maximum voltage. In this…
This paper presents a combination of machine learning techniques to enable prompt evaluation of retired electric vehicle batteries as to either retain those batteries for a second-life application and extend their operation beyond the…
This paper proposes a hierarchical Bayesian model for probabilistic estimation of the electric vehicle battery capacity fade. Since the battery aging factors such as temperature, current, and state of charge are not fixed, and they change…
This paper develops and investigates the impacts of multi-objective Nash optimum (user equilibrium) traffic assignment on a large-scale network for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs) in a…
This paper addresses the challenges of charging infrastructure design (CID) for electrified public transport networks using Battery Electric Buses (BEBs) under conditions of sparse energy consumption data. Accurate energy consumption…
Ubiquitous use of lithium-ion batteries across multiple industries presents an opportunity to explore cost saving initiatives as the price to performance ratio continually decreases in a competitive environment. Manufacturers using…
Accurately predicting the future power demand of electric vehicles is important for developing policy and industrial strategy. Here we propose a method to create a representative set of electricity demand profiles using survey data from…
Data-driven research is becoming a new paradigm in transportation, but the natural lack of individual socio-economic attributes in transportation data makes research such as activity purpose inference and mobility pattern identification…
A vehicle's fuel consumption depends on its type, the speed, the condition, and the gradients of the road on which it is moving. We developed a Routing Engine for finding an eco-route (one with low fuel consumption) between a source and a…
This paper considers energy-aware route planning for a battery-constrained robot operating in environments with multiple recharging depots. The robot has a battery discharge time $D$, and it should visit the recharging depots at most every…
Accurately predicting the future health of batteries is necessary to ensure reliable operation, minimise maintenance costs, and calculate the value of energy storage investments. The complex nature of degradation renders data-driven…
The objective of this research is how an implementation of AI algorithms in the microservices architecture enhances travel itineraries by cost, time, user preferences, and environmental sustainability. It uses machine learning models for…