The velocity regulation of power consumption with traffic lights for electric vehicles

Qingwu Liu, Hongwen He*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Traffic conditions, especially at traffic crossings, have a great impact on the power consumption of vehicles. Regulating velocity using the information between vehicles and traffic systems can decrease the power consumption. This article mainly focuses on an electric vehicle equipped with radar sensors, which can get the traffic information from upto a 100-m-long distance between the controlled vehicle and the traffic lights. Using the information gathered from sensors, the top-level control unit regulates the velocity aiming at lower power consumption. When traveling through crossings, two different traffic conditions are discussed. For the first condition, no other vehicles run between the controlled vehicle and the traffic lights. Only the traffic lights information is considered. For the second condition, the controlled vehicle follows other vehicles to go through the crossing. The information of the nearest front vehicle and traffic lights is taken into consideration. In summary, the traffic lights information, including the controlled vehicle current state, the traffic lights remaining time, and the velocity and distance of the nearest former vehicle (for the second condition) are sent to the top-level control unit. Then, the control unit calculates a velocity list, which will be sent to the vehicle control unit. A simulation is conducted using a traffic simulation software named “Simulation of Urban Mobility” to verify the algorithm. The simulation results indicate that the energy efficiency is improved. For the first condition, the travel time is reduced by 8.27%, and the power consumption is reduced by 18.7%. For the second condition, the power consumption is reduced by 2.96%. Finally, for a 5.8-km driving cycle containing both conditions, the travel time is reduced by 6.9% and electricity consumption is reduced by 9.51%.

Original languageEnglish
Pages (from-to)2312-2322
Number of pages11
JournalProceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Volume233
Issue number9
DOIs
Publication statusPublished - 1 Aug 2019

Keywords

  • Intelligent transportation systems
  • dynamic programming
  • power consumption
  • traffic lights information
  • velocity regulation

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