Optimization of Energy Consumption Based on Traffic Light Constraints and Dynamic Programming

Abstract

Traffic lights are an important part of urban roads. They improve traffic conditions but bring about a limitation of driving speed in the space–time domain for vehicles. In this paper, a traffic light model based on a vehicle–road cooperative system is built. The model provides the vehicle with speed constraints when passing the green light in the time–space domain. A global-optimization-based energy management strategy based on dynamic programming (DP) is constructed with the constraints. The simulations are performed for two driving situations of different signal phases with the electric vehicle driven by a single power source. Compared with the traditional fixed speed driving strategy and green light optimal speed advisory (GLOSA) system, the energy management strategy proposed in this paper is able to control operating points of the motor to be distributed in more efficiency areas. A higher economy is achieved from simulation results.

Modeling and Analyzing the Impact of Different Operating Conditions for Electric and Conventional Vehicles in Malaysia on Energy, Economic, and the Environment

“…A novel approach to optimizing energy consumption in EVs by taking into account traffic lights was also adopted [29]. This study discovers a 24 percent reduction in the energy consumption of EVs when considering the optimal speed profile for EVs while ensuring the vehicle arrives at the traffic light during the green phase.…”

“…During traction, the electrical energy is drawn from the battery and transformed into kinetic energy, and the kinetic energy is transformed into electrical energy during braking through the wheels, thus saving more energy compared to ICEV. There is a 24% reduction in energy consumption of EVs by taking into account the optimal speed profile for EVs at traffic lights, which cannot be conducted in ICEVs [29].…”