Prospects for Plug-in Hybrid Electric Vehicles in the United States and Japan: A General Equilibrium Analysis

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/)The plug-in hybrid electric vehicle (PHEV) may offer a potential near term, low carbon alternative to today's gasoline- and diesel-powered vehicles. A representative vehicle technology that runs on electricity in addition to conventional fuels was introduced into the MIT Emissions Prediction and Policy Analysis (EPPA) model as a perfect substitute for internal combustion engine (ICE-only) vehicles in two likely early-adopting markets, the United States and Japan. We investigate the effect of relative vehicle cost and all-electric range on the timing of PHEV market entry in the presence and absence of an advanced cellulosic biofuels technology and a strong (450ppm) economy-wide carbon constraint. Vehicle cost could be a significant barrier to PHEV entry unless fairly aggressive goals for reducing battery costs are met. If a low cost vehicle is available we find that the PHEV has the potential to reduce CO2 emissions, refined oil demand, and under a carbon policy the required CO2 price in both the United States and Japan. The emissions reduction potential of PHEV adoption depends on the carbon intensity of electric power generation and the size of the vehicle fleet. Thus, the technology is much more effective in reducing CO2 emissions if adoption occurs under an economy-wide cap and trade system that also encourages low-carbon electricity generation.BP Conversion Research Project and the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial sponsors and Federal grants

Electric Power Allocation in a Network of Fast Charging Stations

In order to increase the penetration of electric vehicles, a network of fast charging stations that can provide drivers with a certain level of quality of service (QoS) is needed. However, given the strain that such a network can exert on the power grid, and the mobility of loads represented by electric vehicles, operating it efficiently is a challenging problem. In this paper, we examine a network of charging stations equipped with an energy storage device and propose a scheme that allocates power to them from the grid, as well as routes customers. We examine three scenarios, gradually increasing their complexity. In the first one, all stations have identical charging capabilities and energy storage devices, draw constant power from the grid and no routing decisions of customers are considered. It represents the current state of affairs and serves as a baseline for evaluating the performance of the proposed scheme. In the second scenario, power to the stations is allocated in an optimal manner from the grid and in addition a certain percentage of customers can be routed to nearby stations. In the final scenario, optimal allocation of both power from the grid and customers to stations is considered. The three scenarios are evaluated using real traffic traces corresponding to weekday rush hour from a large metropolitan area in the US. The results indicate that the proposed scheme offers substantial improvements of performance compared to the current mode of operation; namely, more customers can be served with the same amount of power, thus enabling the station operators to increase their profitability. Further, the scheme provides guarantees to customers in terms of the probability of being blocked by the closest charging station. Overall, the paper addresses key issues related to the efficient operation of a network of charging stations.Comment: Published in IEEE Journal on Selected Areas in Communications July 201

Electric vehicle possibilities using low power and light weight range extenders

Electric cars have the disadvantage of a limited range, and drivers may experience a range anxiety. This range anxiety can be solved by adding a range extender. But, the range extender should be light so as not to significantly increase the weight of the original vehicle. In urban areas with dense traffic (usually developing countries), the average speed around cities is typically lower than 50km/h. This means, the rolling resistance losses are more important than aerodynamic losses, and a weight reduction results in a bigger electrical range. Therefore, smaller and lighter range extenders are of much interest. The contribution of this paper is to indicate the possibility of range extenders with less than 25 kg with a capacity of 150 to 200 cc to suit a condition where weight counts. In this paper, the cost, environmental and grid impacts of going electric are also discussed. The effect of high altitude and driving style on the performance of an electric vehicle is assessed. The challenges and opportunities of vehicle electrification between countries with decarbonated power generation and fossil fuel dominated power generation are highlighted. Throughout the article, the case of Ethiopia is taken as an example

Loss analysis of vehicle-to-grid operation

The plug-in hybrid electric vehicle (PHEV) with vehicle-to-grid (V2G) capability is becoming increasingly popular and can be expected to deploy in a large scale. According to the estimation of PHEV penetration degree and the charging characteristics, the modeling of distribution grid with extra load of PHEV charging is formulated first. The PHEVs plugged into the grid, when aggregated in a considerable number, constitute a new load. The impacts of this extra load on the grid are analyzed by power flow simulation in terms of power losses and voltage variation. Uncontrolled charging and optimal charging scenarios are compared in the 33-bus test system. The results indicate the possible problem caused by charging PHEVs and the necessity of building a new control scheme to schedule the generation and the charging profile in the grid. Thus the optimization algorithm is designed to minimize the power losses, and enhance the power quality of the grid as well. The improved model with further constraints for practical application of V2G is discussed. In this model, the ability to schedule both charging and discharging of PHEVs with V2G technology is presented. © Copyright 2011 IEEE - All Rights Reserved.published_or_final_versionThe 2010 IEEE Vehicle Power and Propulsion Conference (VPPC), Lille, France, 1-3 September 2010. In Proceedings of VPPC, 2010, p. 1-

A Novel Learning Based Model Predictive Control Strategy for Plug-in Hybrid Electric Vehicle

The multi-source electromechanical coupling renders energy management of plug-in hybrid electric vehicles (PHEVs) highly nonlinear and complex. Furthermore, the complicated nonlinear management process highly depends on knowledge of driving conditions, and hinders the control strategies efficiently applied instantaneously, leading to massive challenges in energy saving improvement of PHEVs. To address these issues, a novel learning based model predictive control (LMPC) strategy is developed for a serial-parallel PHEV with the reinforced optimal control effect in real time application. Rather than employing the velocity-prediction based MPC methods favored in the literature, an original reference-tracking based MPC solution is proposed with strong instant application capacity. To guarantee the optimal control effect, an online learning process is implemented in MPC via the Gaussian process (GP) model to address the uncertainties during state estimation. The tracking reference in LMPC based control problem in PHEV is achieved by a microscopic traffic flow analysis (MTFA) method. The simulation results validate that the proposed method can optimally manage energy flow within vehicle power sources in real time, highlighting its anticipated preferable performance