Optimal energy allocation strategy for electric vehicles based on the real-time model predictive control technology

2022 ◽  
Vol 50 ◽  
pp. 101797
Author(s):  
Hongqian Wei ◽  
Likang Fan ◽  
Qiang Ai ◽  
Wenqiang Zhao ◽  
Tianyi Huang ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Electric Vehicles ◽  
Energy Allocation ◽  
Control Technology ◽  
Allocation Strategy ◽  
Time Model ◽  
The Real ◽  
Optimal Energy Allocation

scholarly journals Continuous-time Model Predictive Control for Real-time Flexibility Scheduling of Plugin Electric Vehicles

2018 ◽  
Vol 51 (28) ◽  
pp. 498-503 ◽  
Author(s):  
Roohallah Khatami ◽  
Masood Parvania ◽  
Avishan Bagherinezhad
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Electric Vehicles ◽  
Continuous Time ◽  
Continuous Time Model ◽  
Time Model

Real-time model predictive control of connected electric vehicles

2018 ◽  
Vol 57 (11) ◽  
pp. 1720-1743 ◽  
Author(s):  
Mohit Batra ◽  
John McPhee ◽  
Nasser L. Azad
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Electric Vehicles ◽  
Time Model

scholarly journals Real-Time Model Predictive Control of Rigid Body Motion via Discretization Using the Cayley Map

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 17149-17159 ◽  
Author(s):  
Yuichi Tadokoro ◽  
Yuki Taya ◽  
Tatsuya Ibuki ◽  
Mitsuji Sampei
Keyword(s):  
Model Predictive Control ◽  
Rigid Body ◽  
Real Time ◽  
Predictive Control ◽  
Rigid Body Motion ◽  
Body Motion ◽  
Time Model ◽  
Cayley Map

scholarly journals Review and Comparison of Path Tracking Based on Model Predictive Control

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1077 ◽  
Author(s):  
Guoxing Bai ◽  
Yu Meng ◽  
Li Liu ◽  
Weidong Luo ◽  
Qing Gu ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Path Tracking ◽  
Error Model ◽  
The Real ◽  
Time Performance ◽  
Reference Path ◽  
Reference Velocity ◽  
Positioning Errors

Recently, model predictive control (MPC) is increasingly applied to path tracking of mobile devices, such as mobile robots. The characteristics of these MPC-based controllers are not identical due to the different approaches taken during design. According to the differences in the prediction models, we believe that the existing MPC-based path tracking controllers can be divided into four categories. We named them linear model predictive control (LMPC), linear error model predictive control (LEMPC), nonlinear model predictive control (NMPC), and nonlinear error model predictive control (NEMPC). Subsequently, we built these four controllers for the same mobile robot and compared them. By comparison, we got some conclusions. The real-time performance of LMPC and LEMPC is good, but they are less robust to reference paths and positioning errors. NMPC performs well when the reference velocity is high and the radius of the reference path is small. It is also robust to positioning errors. However, the real-time performance of NMPC is slightly worse. NEMPC has many disadvantages. Like LMPC and LEMPC, it performs poorly when the reference velocity is high and the radius of the reference path is small. Its real-time performance is also not good enough.

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