Efficient lithium-ion battery model predictive control using differential flatness-based pseudospectral methods

Ji Liu, Guang Li, Hosam K. Fathy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

This paper proposes an efficient nonlinear model predictive control (NMPC) framework to solve nonconvex lithium-ion battery trajectory optimization problems for battery management systems (BMS). It is challenging to solve these problems online due to complexity and nonconvexity. To address these challenges, we combine four established techniques from the control literature. First, we represent the single particle model (SPM) using orthogonal projection techniques. Second, we exploit the differential flatness of Fick's second law of diffusion to capture all of the dynamics in one electrode using a single scalar trajectory of a "flat output" variable. Third, we optimize the above flat output trajectories using pseudospectral methods. Fourth, we employ the NMPC strategy to solve the battery trajectory optimization problem online. The proposed NMPC framework is demonstrated by solving 2 optimal charging problems accounting for physics-based side reaction constraints and is shown to be twice as computationally efficient as pseudospectral online optimization alone.

Original languageEnglish (US)
Title of host publicationAdaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2
Subtitle of host publicationHybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791857243
DOIs
StatePublished - Jan 1 2015
EventASME 2015 Dynamic Systems and Control Conference, DSCC 2015 - Columbus, United States
Duration: Oct 28 2015Oct 30 2015

Publication series

NameASME 2015 Dynamic Systems and Control Conference, DSCC 2015
Volume1

Other

OtherASME 2015 Dynamic Systems and Control Conference, DSCC 2015
CountryUnited States
CityColumbus
Period10/28/1510/30/15

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Mechanical Engineering
  • Control and Systems Engineering

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    Liu, J., Li, G., & Fathy, H. K. (2015). Efficient lithium-ion battery model predictive control using differential flatness-based pseudospectral methods. In Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems (ASME 2015 Dynamic Systems and Control Conference, DSCC 2015; Vol. 1). American Society of Mechanical Engineers. https://doi.org/10.1115/DSCC2015-9765