Statistical analysis of real-world urban driving cycles for modelling energy consumption of electric vehicles

2016 ◽  
pp. 25-39 ◽  
Author(s):  
Bartłomiej Ohde ◽  
Grzegorz Ślaski ◽  
Michał Maciejewski
Keyword(s):  
Energy Consumption ◽  
Statistical Analysis ◽  
Electric Vehicles ◽  
Real World ◽  
Driving Cycles

Comparative study of real-world driving cycles, energy consumption, and CO2 emissions of electric and gasoline motorcycles driving in a congested urban corridor

2019 ◽  
Vol 45 ◽  
pp. 619-627 ◽  
Author(s):  
Triluck Koossalapeerom ◽  
Thaned Satiennam ◽  
Wichuda Satiennam ◽  
Watis Leelapatra ◽  
Atthapol Seedam ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Comparative Study ◽  
Co2 Emissions ◽  
Real World ◽  
Driving Cycles ◽  
Urban Corridor

scholarly journals Improvement of Battery Life and Energy Economy for Electric Vehicles with Two-Speed Transmission

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3409
Author(s):  
Ying Lyu ◽  
Xuenan Sun ◽  
Hong Chu ◽  
Bingzhao Gao
Keyword(s):  
Energy Consumption ◽  
Electric Vehicles ◽  
Economic Indicator ◽  
Battery Life ◽  
Driving Cycles ◽  
Life Model ◽  
Energy Environment ◽  
Energy Economy ◽  
Simulation Results ◽  
The One

With the current energy environment background and development of the electrification of the automotive industry, a comprehensive economic indicator, in which the battery aging is further considered on the basis of conventional energy consumption, is proposed to research the energy optimization problem of two-speed electric vehicles. Firstly, a battery life model that adapts to vehicles under high dynamic conditions is introduced. Then, the speed optimal control problem of the two-speed electric vehicles in the acceleration–cruise–deceleration process is established and solved. Finally, the simulation results of two different performance indicators are contrasted and the performance improvement of the two-speed gearbox to the electric vehicles is analyzed. The simulation results under various working scenarios and driving cycles demonstrate that, compared with the conventional economic indicator considering the energy consumption only, the proposed economic indicator can significantly improve the battery life. In addition, it can also be seen that, compared with the one-speed electric vehicles, the application of a two-speed gearbox provides better performance from the aspects of battery aging saving and energy consumption.

scholarly journals Effect of Ambient Temperature on Electric Vehicles’ Energy Consumption and Range: Model Definition and Sensitivity Analysis Based on Nissan Leaf Data

2019 ◽  
Vol 10 (1) ◽  
pp. 2 ◽  
Author(s):  
Paolo Iora ◽  
Laura Tribioli
Keyword(s):  
Sensitivity Analysis ◽  
Energy Consumption ◽  
Ambient Temperature ◽  
Electric Vehicles ◽  
Ambient Temperatures ◽  
Battery Model ◽  
Driving Cycles ◽  
Using Data ◽  
Set Up ◽  
The Impact

In this paper, a general quasi-steady backward-looking model for energy consumption estimation of electric vehicles is presented. The model is based on a literature review of existing approaches and was set up using publicly available data for Nissan Leaf. The model has been used to assess the effect of ambient temperature on energy consumption and range, considering various reference driving cycles. The results are supported and validated using data available from an experimental campaign where the Nissan Leaf was driven to depletion across a broad range of winter ambient temperatures. The effect of ambient temperature and the consequent accessories consumption due to cabin heating are shown to be remarkable. For instance, in case of Federal Urban Driving Schedule (FUDS), simplified FUDS (SFUDS), and New European Driving Cycle (NEDC) driving cycles, the range exceeds 150 km at 20 °C, while it reduces to about 85 km and 60 km at 0 °C and −15 °C, respectively. Finally, a sensitivity analysis is reported to assess the impact of the hypotheses in the battery model and of making different assumptions on the regenerative braking efficiency.

Real-world driving cycles and energy consumption informed by large-sized vehicle trajectory data

2019 ◽  
Vol 223 ◽  
pp. 564-574 ◽  
Author(s):  
Ruoyun Ma ◽  
Xiaoyi He ◽  
Yali Zheng ◽  
Boya Zhou ◽  
Sheng Lu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Real World ◽  
Trajectory Data ◽  
Driving Cycles ◽  
Vehicle Trajectory

scholarly journals Energy Consumption Prediction for Electric Vehicles Based on Real-World Data

Energies ◽  
2015 ◽  
Vol 8 (8) ◽  
pp. 8573-8593 ◽  
Author(s):  
Cedric De Cauwer ◽  
Joeri Van Mierlo ◽  
Thierry Coosemans
Keyword(s):  
Energy Consumption ◽  
Electric Vehicles ◽  
Real World ◽  
Real World Data ◽  
World Data ◽  
Energy Consumption Prediction ◽  
Consumption Prediction

scholarly journals Differences in Energy Consumption in Electric Vehicles: An Exploratory Real-World Study in Beijing

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Kezhen Hu ◽  
Jianping Wu ◽  
Tim Schwanen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Electric Vehicles ◽  
Real World ◽  
Time Series Data ◽  
Urban Traffic ◽  
Environmental Benefits ◽  
Series Data ◽  
Traffic Conditions ◽  
Infrastructure Design

Electric vehicles (EVs) are widely regarded as a promising solution to reduce air pollution in cities and key to a low carbon mobility future. However, their environmental benefits depend on the temporal and spatial context of actual usage (journey energy efficiency) and the rolling out of EVs is complicated by issues such as limited range. This paper explores how the energy efficiency of EVs is affected and shaped by driving behavior, personal driving styles, traffic conditions, and infrastructure design in the real world. Tests have been conducted with a Nissan LEAF under a typical driving cycle on the Beijing road network in order to improve understanding of variations in energy efficiency among drivers under different urban traffic conditions. Energy consumption and operation parameters were recorded in both peak and off-peak hours for a total of 13 drivers. The analysis reported in this paper shows that there are clear patterns in energy consumption along a route that are in part related to differences in infrastructure design, traffic conditions, and personal driving styles. The proposed method for analyzing time series data about energy consumption along routes can be used for research with larger fleets of EVs in the future.

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