Convex modeling of energy buffers in power control applications

This paper describes modeling steps for presenting energy buffers as convex models in power control applications. Except obtaining the optimal control, the paper also shows how convex optimization can be used to simultaneously size the energy buffer while optimally controlling a trajectory following system. The energy buffers are capacitors and batteries with quadratic power losses, while the resulting convex problem is a semidefinite program. The convex modeling steps are described through a problem of optimal buffer sizing and control of a hybrid electric vehicle. The studied vehicle is a city bus driven along a perfectly known bus line. The paper also shows modeling steps for alternative convex models where power losses and power limits of the energy buffer are approximated. The approximated models show significant decrease in computation time without visible impact on the optimal result.

[1]  U Zoelch,et al.  Dynamic optimization method for design and rating of the components of a hybrid vehicle , 2014 .

[2]  François Glineur,et al.  Topics in Convex Optimization: Interior-Point Methods, Conic Duality and Approximations , 2001 .

[3]  Jonas Fredriksson,et al.  A methodology and a tool for evaluating hybrid electric powertrain configurations , 2011 .

[4]  Hosam K. Fathy,et al.  Tradeoffs between battery energy capacity and stochastic optimal power management in plug-in hybrid electric vehicles , 2010 .

[5]  Judy Anderson,et al.  Electric and Hybrid Cars: A History , 2004 .

[6]  Lino Guzzella,et al.  Vehicle Propulsion Systems: Introduction to Modeling and Optimization , 2005 .

[7]  Jonas Sjöberg,et al.  Component sizing of a plug-in hybrid electric powertrain via convex optimization , 2012 .

[8]  Huei Peng,et al.  Power management and design optimization of fuel cell/battery hybrid vehicles , 2007 .

[9]  Hosam K. Fathy,et al.  between Battery Energy Capacity and Stochastic Optimal Power Management in Plug-in Hybrid Electric Vehicles I , 2009 .

[10]  Dimitri Peaucelle,et al.  SEDUMI INTERFACE 1.02: a tool for solving LMI problems with SEDUMI , 2002, Proceedings. IEEE International Symposium on Computer Aided Control System Design.

[11]  A. Burke Ultracapacitors: why, how, and where is the technology , 2000 .

[12]  Sean R Eddy,et al.  What is dynamic programming? , 2004, Nature Biotechnology.

[13]  Andrew F. Burke,et al.  Batteries and Ultracapacitors for Electric, Hybrid, and Fuel Cell Vehicles , 2007, Proceedings of the IEEE.

[14]  Olle Sundström,et al.  Torque-Assist Hybrid Electric Powertrain Sizing: From Optimal Control Towards a Sizing Law , 2010, IEEE Transactions on Control Systems Technology.

[15]  Bo Egardt,et al.  Predictive energy management of a 4QT series-parallel hybrid electric bus , 2009 .

[16]  T. C. Moore HEV control strategy: implications of performance criteria, system configuration and design, and component selection , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[17]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.