The Experts below are selected from a list of 168 Experts worldwide ranked by ideXlab platform

Mohamed Z. Youssef - One of the best experts on this subject based on the ideXlab platform.

  • Optimal gear ratios selection for a Nissan Leaf: A case study of InGear transmission system
    2017 IEEE Energy Conversion Congress and Exposition (ECCE), 2017
    Co-Authors: Ahmed S. Abdelrahman, Khalil S. Algarny, Mohamed Z. Youssef
    Abstract:

    In this paper, the impact of transmission gear ratios selection on a Nissan Leaf EV (NLEV) is investigated. The traditional single ratio gearboxes are replaced by multiple ratio ones. The selection of the gear ratio is proved to have a significant impact on electric vehicle's performance and range. A mathematical model of a NLEV is developed for both single and multiple ratio transmission systems. The influence of different gear ratios is studied on Nissan Leaf performance. The simulation results reveal a significant effect on the overall efficiency due to integrating a transmission system with a NLEV. Comparisons are performed for both single and two-speed transmissions and results are quantified and discussed.

  • gan on silicon e hemt and pure silicon mosfet in high frequency switching of ev dc dc converter a comparative study in a Nissan Leaf
    International Telecommunications Energy Conference, 2016
    Co-Authors: Yosra Attia, Mohamed Z. Youssef
    Abstract:

    This paper presents the merits of using low-losses fast-switching, Gallium Nitride on Silicon Enhanced mode High-Electron-Mobility-Transistor cascode switches; in comparison to pure Silicon MOSFET in the DC/DC converter of the Nissan Leaf electric vehicle (EV). The performance of the car, at steady state conditions, is studied to show the technical benefits of using Gallium Nitride on Silicon Enhanced mode High-Electron-Mobility-Transistor cascode as the switching device. This device belongs to a 600 V power semiconductor devices family of high density wide band gap. It achieves extremely efficient power conversion with fast switching slew rates higher than 150 V/ns compared to 50 V/ns for the pure silicon. Moreover, it has low reverse recovery charge that reduces the switch loss significantly compared to its peers of pure silicon. To assess these merits, an EV powertrain model was simulated in PSIM. This model considers the calculation of both switching and conduction losses for each material. The power losses and efficiencies were observed for different junction temperatures. The results showed lower total switches power losses with the GaN switch. This reduction in losses was recorded at different switching frequencies.

  • sic devices performance overview in ev dc dc converter a case study in a Nissan Leaf
    IEEE Transportation Electrification Conference and Expo Asia-Pacific, 2016
    Co-Authors: Yosra Attia, Ahmed S. Abdelrahman, M Hamouda, Mohamed Z. Youssef
    Abstract:

    This paper presents the technical and economical merits of using low losses fast switching Silicon Carbide (SiC) accumulated gate field effect transistor (ACCUFET) switches in comparison with a Hybrid module of Silicon (Si) IGBT with anti-parallel schottky barrier diode (SBD) in DC/DC converter applications of the Nissan Leaf electric vehicle (EV) motor drive. The performance of the car, at steady state conditions, is studied at different temperatures. The power losses, current, voltage, torque and speed results are given. The results showed lower total switching power losses with the SiC ACCUFET. This reduction in losses was recorded at different switching frequencies in comparison to the hybrid switch. The fast switching of SiC Trench ACCUFET reduces current-voltage cross-over losses and enables high frequency operation thus achieving high record efficiency. The high frequency operation will result in a smaller foot print of the converter together with a weight reduction; thus making the car lighter. It is expected that a lighter car will result in a longer range Nissan Leaf with the same battery. Increasing the car mileage of the battery and lowering the cost of magnetic components in the EV will surpass the higher cost of the SiC ACCUFET from an economical point of view.

Tiejiang Yuan - One of the best experts on this subject based on the ideXlab platform.

  • design and assessment of an electric vehicle powertrain model based on real world driving and charging cycles
    IEEE Transactions on Vehicular Technology, 2019
    Co-Authors: Wenping Cao, Zhengyu Lin, Tiejiang Yuan
    Abstract:

    In this paper, an advanced analytical model for an electric vehicle (EV) powertrain has been developed to illustrate the vehicular dynamics by combining electrical and mechanical models in the analysis. This study is based on a Nissan Leaf EV. In the electrical system, the powertrain has various components including a battery pack, a battery management system, a dc/dc converter, a dc/ac inverter, a permanent magnet synchronous motor, and a control system. In the mechanical system, it consists of power transmissions, axial shaft, and vehicle wheels. Furthermore, the driving performance of the Nissan Leaf is studied through the real-world driving tests and simulation tests in MATLAB/Simulink. In the analytical model, the vehicular dynamics is evaluated against changes in the vehicle velocity and acceleration, state of charge of the battery, and the motor power. Finally, a number of EVs involved in the power dispatch is studied. The greenhouse gas emissions of the EV are analyzed according to various energy power and driving features, and compared with the conventional internal combustion engine vehicle. In this case, Nissan Leaf is a pure EV. For a given drive cycle, Nissan Leaf can reduce CO2 emissions by 70%, depending on the way electricity is generated and duty cycles.

Graham Town - One of the best experts on this subject based on the ideXlab platform.

  • a real time range indicator for evs using web based environmental data and sensorless estimation of regenerative braking power
    IEEE Transactions on Vehicular Technology, 2018
    Co-Authors: Kaveh Sarrafan, Kashem M Muttaqi, D Sutanto, Graham Town
    Abstract:

    Most of the commercially available range indicator systems for electric vehicles (EVs) do not provide a sufficiently accurate range to destination, as the environmental factors and driver's behavior are generally not taken into account. In this paper, a real-time range indicator system is developed and implemented using online environmental data from various internet resources to estimate accurately the real-time state of charge and the remaining range for the EV while it is on the road. The estimation considers 1) the dynamic wind speed and wind direction with respect to vehicle position, 2) the probability of rain and ambient temperature, 3) the dynamic effective rolling resistance and terrain adhesion coefficient (based on the condition of the road surface), 4) the time-domain efficiency analysis of the propulsion system, 5) the online traffic conditions and auxiliary loads, and 6) the braking force distribution used in commercially available EVs. The real-time range indicator system is validated using measured data from a 2012 Nissan Leaf driven along a selected route in Australia with the maximum error of 8% for the entire route and less than 1% error at the destination.

John Smart - One of the best experts on this subject based on the ideXlab platform.

  • where do Nissan Leaf drivers in the ev project charge when they have the opportunity to charge at work
    2014
    Co-Authors: John Smart, Don Scoffield
    Abstract:

    This paper invesigates where Nissan Leaf drivers in the EV Project charge when they have the opportunity to charge at work. Do they charge at work, home, or some other location?

  • battery electric vehicle driving and charging behavior observed early in the ev project
    SAE International Journal of Alternative Powertrains, 2012
    Co-Authors: John Smart, Stephen Schey
    Abstract:

    As concern about society's dependence on petroleum-based transportation fuels increases, many see plug-in electric vehicles (PEV) as enablers to diversifying transportation energy sources. These vehicles, which include plug-in hybrid electric vehicles (PHEV), range-extended electric vehicles (EREV), and battery electric vehicles (BEV), draw some or all of their power from electricity stored in batteries, which are charged by the electric grid. In order for PEVs to be accepted by the mass market, electric charging infrastructure must also be deployed. Charging infrastructure must be safe, convenient, and financially sustainable. Additionally, electric utilities must be able to manage PEV charging demand on the electric grid. In the Fall of 2009, a large scale PEV infrastructure demonstration was launched to deploy an unprecedented number of PEVs and charging infrastructure. This demonstration, called The EV Project, is led by Electric Transportation Engineering Corporation (eTec) and funded by the U.S. Department of Energy. eTec is partnering with Nissan North America to deploy up to 4,700 Nissan Leaf BEVs and 11,210 charging units in five market areas in Arizona, California, Oregon, Tennessee, and Washington. With the assistance of the Idaho National Laboratory, eTec will collect and analyze data to characterize vehicle consumer driving and charging behavior, evaluatemore » the effectiveness of charging infrastructure, and understand the impact of PEV charging on the electric grid. Trials of various revenue systems for commercial and public charging infrastructure will also be conducted. The ultimate goal of The EV Project is to capture lessons learned to enable the mass deployment of PEVs. This paper is the first in a series of papers documenting the progress and findings of The EV Project. This paper describes key research objectives of The EV Project and establishes the project background, including lessons learned from previous infrastructure deployment and PEV demonstrations. One such previous study was a PHEV demonstration conducted by the U.S. Department of Energy's Advanced Vehicle Testing Activity (AVTA), led by the Idaho National Laboratory (INL). AVTA's PHEV demonstration involved over 250 vehicles in the United States, Canada, and Finland. This paper summarizes driving and charging behavior observed in that demonstration, including the distribution of distance driven between charging events, charging frequency, and resulting proportion of operation charge depleting mode. Charging demand relative to time of day and day of the week will also be shown. Conclusions from the PHEV demonstration will be given which highlight the need for expanded analysis in The EV Project. For example, the AVTA PHEV demonstration showed that in the absence of controlled charging by the vehicle owner or electric utility, the majority of vehicles were charged in the evening hours, coincident with typical utility peak demand. Given this baseline, The EV Project will demonstrate the effects of consumer charge control and grid-side charge management on electricity demand. This paper will outline further analyses which will be performed by eTec and INL to documenting driving and charging behavior of vehicles operated in a infrastructure-rich environment.« less

Wenping Cao - One of the best experts on this subject based on the ideXlab platform.

  • design and assessment of an electric vehicle powertrain model based on real world driving and charging cycles
    IEEE Transactions on Vehicular Technology, 2019
    Co-Authors: Wenping Cao, Zhengyu Lin, Tiejiang Yuan
    Abstract:

    In this paper, an advanced analytical model for an electric vehicle (EV) powertrain has been developed to illustrate the vehicular dynamics by combining electrical and mechanical models in the analysis. This study is based on a Nissan Leaf EV. In the electrical system, the powertrain has various components including a battery pack, a battery management system, a dc/dc converter, a dc/ac inverter, a permanent magnet synchronous motor, and a control system. In the mechanical system, it consists of power transmissions, axial shaft, and vehicle wheels. Furthermore, the driving performance of the Nissan Leaf is studied through the real-world driving tests and simulation tests in MATLAB/Simulink. In the analytical model, the vehicular dynamics is evaluated against changes in the vehicle velocity and acceleration, state of charge of the battery, and the motor power. Finally, a number of EVs involved in the power dispatch is studied. The greenhouse gas emissions of the EV are analyzed according to various energy power and driving features, and compared with the conventional internal combustion engine vehicle. In this case, Nissan Leaf is a pure EV. For a given drive cycle, Nissan Leaf can reduce CO2 emissions by 70%, depending on the way electricity is generated and duty cycles.