Robust Vehicle Speed Control Using Disturbance Observer in Hybrid Electric Vehicles

2020 ◽  
Vol 21 (4) ◽  
pp. 931-942
Author(s):  
Sangjoon Kim ◽  
Jae Sung Bang ◽  
Sungdeok Kim ◽  
Hyeongcheol Lee
Keyword(s):  
Electric Vehicles ◽  
Disturbance Observer ◽  
Hybrid Electric Vehicles ◽  
Speed Control ◽  
Vehicle Speed ◽  
Hybrid Electric

scholarly journals Optimal Speed Control of Hybrid Electric Vehicles

2011 ◽  
Vol 11 (4) ◽  
pp. 393-400 ◽  
Author(s):  
Anil Kumar Yadav ◽  
Prerna Gaur ◽  
Shyama Kant Jha ◽  
J.R.P. Gupta ◽  
A.P. Mittal
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Speed Control ◽  
Optimal Speed ◽  
Hybrid Electric

Eco-Trajectory Planning with Consideration of Queue along Congested Corridor for Hybrid Electric Vehicles

2019 ◽  
Vol 2673 (9) ◽  
pp. 277-286 ◽  
Author(s):  
Zhen Yang ◽  
Yiheng Feng ◽  
Xun Gong ◽  
Ding Zhao ◽  
Jing Sun
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicles ◽  
Trajectory Planning ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Urban Traffic ◽  
Vehicle Speed ◽  
Speed Profile ◽  
Driving Model ◽  
Hybrid Electric

At signalized intersections, vehicle speed profile plays a vital role in determining fuel consumption and emissions. With advances of connected and automated vehicle technology, vehicles are able to receive predicted traffic information from the infrastructure in real-time to plan their trajectories in a fuel-efficient way. In this paper, an eco-driving model is developed for hybrid electric vehicles in a congested urban traffic environment. The vehicle queuing process is explicitly modeled by the shockwave profile model with consideration of vehicle deceleration and acceleration to provide a green window for eco-vehicle trajectory planning. A trigonometric speed profile is applied to minimize fuel consumption and maximize driving comfort with a low jerk. A hybrid electric vehicle fuel consumption model is built and calibrated with real vehicle data to evaluate the energy benefit of the eco-vehicles. Simulation results from a real-world corridor of six intersections show that the proposed eco-driving model can significantly reduce energy consumption by 8.7% on average and by 23.5% at maximum, without sacrificing mobility.

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