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Poster Session Ⅰ: ICT-Future Vehicle

Model Predictive Control for Minimizing Trip-time and Energy-consumption of Electric Vehicles

초록

영어

This paper presents methods of model predictive control (MPC) for eco-driving minimizing trip-time and energy- consumption of electric vehicles (EVs). Considering both non- convex and convex optimization problem formulations for MPC- based eco-driving, we compare the performances of nonlinear and linear MPC solutions for high-level planning of vehicle speed and charging in a driving simulation of a Munich– Cologne trip (573 km). The linear MPC can be considered as a convex quadratic programming approximation (i.e., convexified quadratic program) of the original nonlinear MPC, but its performance of optimality is shown to be comparable to the nonlinear counterparts whereas its computation speed is one order of magnitude faster.

목차

Abstract
I. INTRODUCTION
II. OPTIMAL CONTROL PROBLEM
A. Modeling
B. Nonconvex OCP 1
C. Nonconvex OCP 2
D. Convex OCP
III. SOLUTION METHODS
A. Nonlinear MPC
B. Linear MPC
IV. SIMULATION RESULTS
A. Nonlinear MPC
B. Linear MPC
V. CONCLUSIONS AND FUTURE WORK
REFERENCES

저자정보

  • Sunwoo Kim Dept. of ECE Inha University
  • Wonhyung Lee Dept. of ECE Inha University
  • Kwang-Ki K. Kim Dept. of ECE Inha University

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