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Multiphase mixed-integer nonlinear optimal control of hybrid electric vehicles

Nicolò Robuschi, Clemens Zeile, Sebastian Säger, Francesco Braghin

2020Automatica61 citationsDOIOpen Access PDF

Abstract

This study considers the problem of computing a non-causal minimum-fuel energy management strategy for a hybrid electric vehicle on a given driving cycle. Specifically, we address the multiphase mixed-integer nonlinear optimal control problem that arises when the optimal gear choice, torque split and engine on/off controls are sought in off-line evaluations. We propose an efficient model by introducing vanishing constraints and a phase specific right-hand side function that accounts for the different powertrain operating modes. The gearbox and driveability requirements translate into combinatorial constraints. These constraints have not been included in previous research; however, they are part of the algorithmic framework for this investigation. We devise a tailored algorithm to solve this problem by extending the combinatorial integral approximation (CIA) technique that breaks down the original mixed-integer nonlinear program into a sequence of nonlinear programs and mixed-integer linear programs, followed by a discussion of its approximation error. Finally, numerical results illustrate the proposed algorithm in terms of solution quality and run time.

Topics & Concepts

Integer (computer science)Nonlinear systemMathematical optimizationOptimal controlFunction (biology)Computer scienceControl theory (sociology)MathematicsControl (management)Artificial intelligencePhysicsBiologyQuantum mechanicsEvolutionary biologyProgramming languageElectric and Hybrid Vehicle TechnologiesElectric Vehicles and InfrastructureAdvanced Combustion Engine Technologies
Multiphase mixed-integer nonlinear optimal control of hybrid electric vehicles | Litcius