scholarly journals Battery Electric Vehicle Fast Charging–Evidence from the Norwegian Market

2020 ◽  
Vol 11 (2) ◽  
pp. 38 ◽  
Author(s):  
Erik Figenbaum
Keyword(s):  
Electric Vehicle ◽  
Thermal Management ◽  
Battery Electric Vehicle ◽  
Passenger Vehicle ◽  
Charging System ◽  
Battery Thermal Management ◽  
Large Spread ◽  
Fast Charging ◽  
Vehicle Fleet ◽  
Low Charge

Norway is the largest Battery Electric Vehicle (BEV) market in the world per capita. The share of the passenger vehicle fleet passed 9.4% at the end of 2019, and users have access to 1500 Combined Charging System (CCS)/Chademo standard fast chargers located in more than 500 different locations. This paper analyses the usage pattern of these fast chargers using a dataset from two large operators covering most of their charging events between Q1 2016 and Q1 2018. The target of the analysis was to understand the fundamental factors that drive the demand for fast charging and influences the user experience, so that they can be taken into account when dimensioning charge facilities, and when designing vehicles. The data displays clear variations in charge power, charge time and charged energy between winter and summer, and a large spread of results due to the BEV models different technical characteristics. The charge power is clearly reduced in the winter compared to the summer, while the charge time is longer. Some charge events have a particularly low charge power which may be due to users fast charging a cold battery at a high State of Charge (SOC) in a vehicle with passive battery thermal management.

scholarly journals The remaining CO2 budget: a comparison of the CO2 emissions of diesel and BEV drivetrain technology

2021 ◽  
Author(s):  
Christian Böhmeke ◽  
Thomas Koch
Keyword(s):  
Electric Vehicle ◽  
Carbon Footprint ◽  
Electricity Generation ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Battery Electric Vehicle ◽  
Useful Life ◽  
Vehicle Fleet ◽  
Real Time Simulations ◽  
Diesel Vehicle

AbstractThis paper describes the CO2 emissions of the additional electricity generation needed in Germany for battery electric vehicles. Different scenarios drawn up by the transmission system operators in past and for future years for expansion of the energy sources of electricity generation in Germany are considered. From these expansion scenarios, hourly resolved real-time simulations of the different years are created. Based on the calculations, it can be shown that even in 2035, the carbon footprint of a battery electric vehicle at a consumption of 22.5 kWh/100 km including losses and provision will be around 100 g CO2/km. Furthermore, it is shown why the often-mentioned German energy mix is not suitable for calculating the emissions of a battery electric vehicle fleet. Since the carbon footprint of a BEV improves significantly over the years due to the progressive expansion of renewable-energy sources, a comparison is drawn at the end of this work between a BEV (29.8 tons of CO2), a conventional diesel vehicle (34.4 tons of CO2), and a diesel vehicle with R33 fuel (25.8 tons of CO2) over the entire useful life.

scholarly journals Evaluation of Fast Charging Efficiency under Extreme Temperatures

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1937 ◽  
Author(s):  
Germana Trentadue ◽  
Alexandre Lucas ◽  
Marcos Otura ◽  
Konstantinos Pliakostathis ◽  
Marco Zanni ◽  
...  
Keyword(s):  
Ambient Temperature ◽  
Electric Vehicle ◽  
Power Conversion ◽  
Weather Conditions ◽  
Extreme Temperatures ◽  
Charging Infrastructure ◽  
Charging System ◽  
Fast Charging ◽  
Electric Vehicle Adoption ◽  
Charging Stations

Multi-type fast charging stations are being deployed over Europe as electric vehicle adoption becomes more popular. The growth of an electrical charging infrastructure in different countries poses different challenges related to its installation. One of these challenges is related to weather conditions that are extremely heterogeneous due to different latitudes, in which fast charging stations are located and whose impact on the charging performance is often neglected or unknown. The present study focused on the evaluation of the electric vehicle (EV) charging process with fast charging devices (up to 50 kW) at ambient (25 °C) and at extreme temperatures (−25 °C, −15 °C, +40 °C). A sample of seven fast chargers and two electric vehicles (CCS (combined charging system) and CHAdeMO (CHArge de Move)) available on the commercial market was considered in the study. Three phase voltages and currents at the wall socket, where the charger was connected, as well as voltage and current at the plug connection between the charger and vehicle have been recorded. According to SAE (Society of Automotive Engineers) J2894/1, the power conversion efficiency during the charging process has been calculated as the ratio between the instantaneous DC power delivered to the vehicle and the instantaneous AC power supplied from the grid in order to test the performance of the charger. The inverse of the efficiency of the charging process, i.e., a kind of energy return ratio (ERR), has been calculated as the ratio between the AC energy supplied by the grid to the electric vehicle supply equipment (EVSE) and the energy delivered to the vehicle’s battery. The evaluation has shown a varied scenario, confirming the efficiency values declared by the manufacturers at ambient temperature and reporting lower energy efficiencies at extreme temperatures, due to lower requested and, thus, delivered power levels. The lowest and highest power conversion efficiencies of 39% and 93% were observed at −25 °C and ambient temperature (+25 °C), respectively.

Hybrid Electric Vehicle Energy Management With Battery Thermal Considerations Using Multi-Rate Dynamic Programming

2013 ◽  
Author(s):  
Rajit Johri ◽  
Wei Liang ◽  
Ryan McGee
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicle ◽  
Thermal Management ◽  
Hybrid Electric Vehicle ◽  
Computational Time ◽  
Bulk Temperature ◽  
Thermal Dynamics ◽  
Battery Thermal Management ◽  
Battery Capacity ◽  
Hybrid Electric

Battery capacity and battery thermal management control have a significant impact on the Hybrid Electric Vehicle (HEV) fuel economy. Additionally, battery temperature has a key influence on the battery health in an HEV. In the past, battery temperature and cooling capacity has not been included while performing optimization studies for power management or optimal battery sizing. This paper presents an application of Dynamic Programming (DP) to HEV optimization with battery thermal constraints. The optimization problem is formulated with 3 state variables, namely, the battery State Of Charge (SOC), the engine speed and the battery bulk temperature. This optimization is critical for determining appropriate battery size and battery thermal management design. The proposed problem has a major challenge in computation time due to the large state space. The paper describes a novel multi-rate DP algorithm to reduce the computational challenges associated with the particular class of large-scale problem where states evolve at very different rates. In HEV applications, the battery thermal dynamics is orders of magnitude slower than powertrain dynamics. The proposed DP algorithm provides a novel way of tackling this problem with multiple time rates for DP with each time rate associated with the fast and slow states separately. Additionally, the paper gives possible numerical techniques to reduce the DP computational time and the time reduction for each technique is shown.

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