A probabilistic approach for determining the influence of urban traffic management policies on energy consumption and greenhouse gas emissions from a battery electric vehicle

Fernández, Roberto Álvarez; Caraballo, Sergio Corbera; López, Francesc Clar

doi:10.1016/j.jclepro.2019.117604

Cited by 27 publications

(8 citation statements)

References 28 publications

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“…The analysis of the amount of energy recovered during braking indicates a reduction in the energy recovery along with the increasing average speed of the test run. Another aspect influencing the energy consumption is the traffic management strategy that changes the speed profiles of the vehicle [13]. The probabilistic approach analyzing four different infrastructure scenarios indicates varied energy consumption and proposes the application of the developed model in further works.…”

Section: Ev-battery Energy Saving Conventional Vehicle-fuel Energy Saving Conventional Vehicle-engine Mech Energy Savingmentioning

confidence: 99%

The possibility of energy consumption reduction using the ECO driving mode based on the RDC test

Cieślik¹,

Szwajca²,

Golimowski³

2020

Combustion Engines

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The greenhouse effect and overall climate changes are the main reasons for developing ecological powertrain units dedicated to road vehicles. An electrical drivetrain without using conventional combustion engines fueled by hydrocar-bon fuels is an effective method to significantly reduce CO2 emissions from the fleet. It is particularly vital in 2020 emis-sion regulations aspects, and continuously the number of vehicles increasing. In this paper battery electric drive system of a small size passenger car was analyzed in terms of two different drive modes in cooperation with two recuperative braking modes. The research was carried out with real driving condition test requirements and driving parameters re-cording. Based on data obtained from OBD signals, energy flow and torque distribution have been specified. In results, overall reducing energy consumption has been achieved with ECO mode compared to normal mode. Selection of the driving mode ECO has a positive impact on reducing the state of charge saving more than 5%, taking into account the whole RDC test; greater energy consumption reductions were observed in selected test areas.

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Section: Ev-battery Energy Saving Conventional Vehicle-fuel Energy Saving Conventional Vehicle-engine Mech Energy Savingmentioning

confidence: 99%

The possibility of energy consumption reduction using the ECO driving mode based on the RDC test

Cieślik¹,

Szwajca²,

Golimowski³

2020

Combustion Engines

View full text Add to dashboard Cite

show abstract

“…So far, a lot of papers about the energy consumption of electric vehicles with different themes have been published [10][11][12][13][14][15][16][17][18][19][20][21]. For example, Fernández determines the influence of urban traffic management policies on energy consumption [10]. Al-Wreikat Yazan evaluates how driving behavior and trip condition effects the energy consumption [12].…”

Section: Introductionmentioning

confidence: 99%

Energy Consumption Prediction of Electric Vehicles Based on Digital Twin Technology

Zhang

Zou

Zhou

et al. 2021

WEVJ

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Digital twinning technology originated in the field of aerospace. The real-time and bidirectional feature of data interaction guarantees its advantages of high accuracy, real-time performance and scalability. In this paper the digital twin technology was introduced to electric vehicle energy consumption research. First, an energy consumption model of an electric vehicle of BAIC BJEV was established, then the model was optimized and verified through the energy consumption data of the drum test. Based on the data of the vehicle real-time monitoring platform, a digital twin model was built, and it was trained and updated by daily new data. Eventually it can be used to predict and verify the data of vehicle. In this way the prediction of energy consumption of vehicles can be achieved.

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“…Transportation is one important component of urban systems. Due to the large population and active economic activities in cities, the transportation system is often under pressure, resulting in unhealthy conditions, such as traffic congestion [ 11 , 12 , 13 , 14 , 15 ]. Therefore, the healthy status of transportation systems in major cities in China has been examined in the Urban Health Assessment program [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Vulnerability and Resilience of Urban Traffic to Precipitation in China

Zhang

Liu

Ying

et al. 2021

IJERPH

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The concept of Healthy Cities, introduced by the World Health Organization, demonstrates the value of health for the whole urban system. As one of the most important components of urban systems, transportation plays an important role in Healthy Cities. Many transportation evaluation systems focus on factors such as road networks, parking spaces, transportation speed, accessibility, convenience, and commuting time, while the vulnerability and resilience of urban transportation are rarely evaluated. This study presents the preliminary progress in the evaluation of traffic vulnerability and resilience during precipitation events in 39 Chinese cities. Traffic congestion index data, derived from the Baidu Map Smart Transportation Platform, and rainfall data, derived from NASA’s global precipitation measurement, are utilized. Traffic vulnerability index, traffic resilience index, and the corresponding quantitative methods are proposed, and the analysis results are presented. This study is of value in improving the understanding of urban traffic vulnerability and resilience, and in enabling the quantitative evaluation of them in urban health assessment and the Healthy Cities program.

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A probabilistic approach for determining the influence of urban traffic management policies on energy consumption and greenhouse gas emissions from a battery electric vehicle

Cited by 27 publications

References 28 publications

The possibility of energy consumption reduction using the ECO driving mode based on the RDC test

The possibility of energy consumption reduction using the ECO driving mode based on the RDC test

Energy Consumption Prediction of Electric Vehicles Based on Digital Twin Technology

Vulnerability and Resilience of Urban Traffic to Precipitation in China

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