scholarly journals Model-Predictive Optimization for Pure Electric Vehicle during a Vehicle-Following Process

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Sheng Zhang ◽  
Xiangtao Zhuan
Keyword(s):  
Energy Consumption ◽  
Multiobjective Optimization ◽  
Electric Vehicle ◽  
Predictive Control ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Change Rate ◽  
Upper Level ◽  
Reduction Of Energy Consumption ◽  
Reference Trajectories

In this paper, a pure electric vehicle (PEV) equipped with adaptive cruise control (ACC) system is studied for a vehicle-following process. And a multiobjective optimization algorithm for ACC system is proposed in a model-predictive control (MPC) framework for optimizing safety, tracking capability, driving comfortability and energy consumption. The longitudinal dynamics of the ACC system are modeled, which not only considers the vehicle spacing and speed, but also introduces the acceleration and the change rate of acceleration (jerk) for the host vehicle and fully considers the influence of the acceleration of the leading vehicle. The improvement of driving comfortability and the reduction of energy consumption are achieved mainly by optimizing the acceleration and jerk of host vehicle. Some optimized reference trajectories are introduced to MPC for improving driving comfortability of host vehicle. The performances of the multiobjective upper level algorithm combined with the PEV model are evaluated for three representative scenarios. The results demonstrate the effectiveness of the proposed algorithm.

scholarly journals Study on Adaptive Cruise Control Strategy for Battery Electric Vehicle

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Sheng Zhang ◽  
Xiangtao Zhuan
Keyword(s):  
Energy Consumption ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Adaptive Cruise Control ◽  
Simulation Experiment ◽  
Hierarchical Control ◽  
Battery Electric Vehicle ◽  
Cruise Control ◽  
Car Following ◽  
Energy Economy

This paper studies the control strategy for adaptive cruise control (ACC) system on a battery electric vehicle (BEV) in the car-following process, and the highlight of this paper is that the regeneration braking of BEV is considered in the car-following process. The hierarchical control structure is adopted for the ACC system. And the structure contains an upper controller and a lower controller. In the upper controller, multiple objectives including the safety, tracking, comfort, and energy consumption are optimized by using the model predictive control (MPC) method. In the lower controller, the energy is recovered during braking. So the energy economy is improved by reducing energy consumption and increasing energy recovery. The proposed ACC strategy is evaluated in simulation experiment. In the simulation experiment, safe tracking for the front vehicle is guaranteed, and the comfort and the energy economy are improved greatly. So the proposed adaptive cruise control strategy can make ACC more widely used in BEVs.

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