Electric Vehicles

Velocity Predictors for Predictive Energy Management in Hybrid Electric Vehicles

Sun, Chao
Hu, Xiaosong
Scott Moura
Sun, Fengchun
2015

The performance and practicality of predictive energy management in hybrid electric vehicles (HEVs) are highly dependent on the forecast of future vehicular velocities, both in terms of accuracy and computational efficiency. In this brief, we provide a comprehensive comparative analysis of three velocity prediction strategies, applied within a model predictive control framework. The prediction process is performed over each receding horizon, and the predicted velocities are utilized for fuel economy optimization of a power-split HEV. We assume that no telemetry or on-board sensor...

Integrating Traffic Velocity Data into Predictive Energy Management of Plug-in Hybrid Electric Vehicles

Sun, Chao
Sun, Fengchun
Hu, Xiaosong
Hedrick, J. Karl
Scott Moura
2015

Recent advances in the traffic monitoring systems have made traffic velocity information accessible in real time. This paper proposes a supervised predictive energy management framework aiming to improve the fuel economy of a power-split plug-in hybrid electric vehicle (PHEV) by incorporating dynamic traffic feedback data. Compared with conventional model predictive control (MPC), an additional supervisory state of charge (SOC) planning level is constructed in this framework. A power balance PHEV model is developed for this upper level to rapidly generate optimal battery SOC trajectories,...

Optimal Charging of Vehicle-to-Grid Fleets via PDE Aggregation Techniques

Le Floch, Caroline
Di Meglio, Florent
Scott Moura
2015

This paper examines modeling and control of a large population of grid-connected plug-in electric vehicles (PEVs). PEV populations can be leveraged to provide valuable grid services when managed via model-based control. However, such grid services cannot sacrifice a PEV's primary purpose - mobility. We consider a centrally located fleet of identical PEVs that are distributed to and collected from drivers. The fleet also provides regulation services to the grid, contracted a priori. We develop a partial differential equation (PDE)- based technique for aggregating large populations of PEVs....

Charging Ahead on the Transition to Electric Vehicles with Standard 120V Wall Outlets

Saxena, Samveg
MacDonald, Jason
Scott Moura
2015

Electrification of transportation is needed soon and at significant scale to meet climate goals, but electric vehicle adoption has been slow and there has been little systematic analysis to show that today’s electric vehicles meet the needs of drivers. We apply detailed physics-based models of electric vehicles with data on how drivers use their cars on a daily basis. We show that the energy storage limits of today’s electric vehicles are outweighed by their high efficiency and the fact that driving in the United States seldom exceeds 100km of daily travel. When accounting for these...

Optimal Charging of Electric Vehicles for Load Shaping: A Dual-Splitting Framework With Explicit Convergence Bounds

Le Floch, Caroline
Belletti, Francois
Scott Moura
2016

This paper proposes a tailored distributed optimal charging algorithm for plug-in electric vehicles (PEVs). If controlled properly, large PEV populations can enable high penetration of renewables by balancing loads with intermittent generation. The algorithmic challenges include scalability, computation, uncertainty, and constraints on driver mobility and power-system congestion. This paper addresses computation and communication challenges via a scalable distributed optimal charging algorithm. Specifically, we exploit the mathematical structure of the aggregated charging problem to...

Coordination of V2G and Distributed Wind Power Using the Storage-like Aggregate PEV Model

Zhang, Hongcai
Hu, Zechun
Song, Yonghua
Scott Moura
2016

A plug-in electric vehicle (PEV) fleet utilizing vehicle-to-grid (V2G) technology, i.e., a V2G fleet, can behave as a storage system, e.g., promoting integration of distributed wind power resources. However, because the PEVs' behaviors are stochastic and a V2G fleet's population is large, three technical difficulties hinder the utilization of V2G: charging demand forecasting; ahead-of-time charge and discharge scheduling; real-time charge and discharge power dispatching. This paper utilizes a storage-like aggregate model (SLAM) of a V2G fleet that employs aggregated parameters to represent...

Optimal Routing and Charging of Electric Ride-Pooling Vehicles in Urban Networks

Nicolas, Léa
Scott Moura
2016

In this project, we study an Electric Vehicle Routing Problem with Pick-ups and Deliveries, Time Windows, and Recharging Stations on New York City Taxicab data. In order to solve this problem, we divide the problems into three phases: (i) grouping similar customer requests by identifying geographic zones and time slots; (ii) determine groups of passengers to be transported together; (iii) complete the vehicle itinerary between these groups of passengers. The first phase uses the clustering method k-means  on the locations of pick-ups and deliveries of New York City taxicabs in...

Stochastic Control of Smart Home Energy Management with Plug-in Electric Vehicle Battery Energy Storage and Photovoltaic Array

Wu, Xiaohua
Hu, Xiaosong
Scott Moura
Yin, Xiaofeng
Pickert, Volker
2016

Energy management strategies are instrumental in the performance and economy of smart homes integrating renewable energy and energy storage. This article focuses on stochastic energy management of a smart home with PEV (plug-in electric vehicle) energy storage and photovoltaic (PV) array. It is motivated by the challenges associated with sustainable energy supplies and the local energy storage opportunity provided by vehicle electrification. This paper seeks to minimize a consumer's energy charges under a time-of-use tariff, while satisfying home power demand and PEV charging requirements...

A Second Order Cone Programming Model for PEV Fast-Charging Station Planning

Zhang, Hongcai
Scott Moura
Hu, Zechun
Qi, Wei
Song, Yonghua
2017

This paper studies siting and sizing of plug-in electric vehicle (PEV) fast-charging stations on coupled transportation and power networks. We develop a closed-form service rate model of highway PEV charging stations' service abilities, which considers heterogeneous PEV driving ranges and charging demands.We utilize a modified capacitated flow refueling location model (CFRLM) to explicitly capture time-varying PEV charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM to enhance model accuracy and computational efficiency....

Joint Planning of PEV Fast-Charging Network and Distributed PV Generation

Zhang, Hongcai
Scott Moura
Hu, Zechun
Qi, Wei
2017

Integration of plug-in electric vehicles (PEVs) with distributed renewable resources will decrease PEVs' well-to-wheels greenhouse gas emissions, promote renewable power adoption and defer power system investments. This paper proposes a multidisciplinary approach to jointly planning PEV fast-charging stations and distributed photovoltaic (PV) power plants on coupled transportation and power networks. First, we develop models of 1) PEV fast-charging stations; 2) highway transportation networks under PEV driving range constraints; 3) PV power plants with reactive power control. Then, we...