Combined design and control optimization of hybrid vehicles
Book chapter, 2015

Hybrid vehicles play an important role in reducing energy consumption and pollutant emissions of ground transportation. The increased mechatronic system complexity, however, results in a heavy challenge for efficient component sizing and power coordination among multiple power sources. This chapter presents a convex programming framework for the combined design and control optimization of hybrid vehicles. An instructive and straightforward case study of design and energy control optimization for a fuel cell/supercapacitor hybrid bus is delineated to demonstrate the effectiveness and the computational advantage of the convex programming methodology. Convex modeling of key components in the fuel cell/supercapactior hybrid powertrain is introduced, while a pseudo code in CVX is also provided to elucidate how to practically implement the convex optimization. The generalization, applicability, and validity of the convex optimization framework are also discussed for various powertrain configurations (i.e., series, parallel, and series-parallel), different energy storage systems (e.g., battery, supercapacitor, and dual buffer), and advanced vehicular design and controller synthesis accounting for the battery thermal and aging conditions. The proposed methodology is an efficient tool that is valuable for researchers and engineers in the area of hybrid vehicles to address realistic optimal control problems.

fuel cell

hybrid electric vehicle

optimal control

energy storage system

convex optimization

component sizing

energy management


Nikolce Murgovski

Chalmers, Signals and Systems, Systems and control

Xiaosong Hu

Chalmers, Signals and Systems, Systems and control

Lars Johannesson

Chalmers, Signals and Systems, Systems and control

Bo Egardt

Chalmers, Signals and Systems, Systems and control

Handbook of Clean Energy Systems

9781118991978 (ISBN)

Driving Forces

Sustainable development

Areas of Advance



Subject Categories

Energy Engineering

Computational Mathematics

Control Engineering



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