Control Strategy Optimization for a Series Hybrid Vehicle

Konev, Anton; Lezhnev, L. Yu.; Kolmanovsky, Ilya

doi:10.4271/2006-01-0663

Cited by 34 publications

(21 citation statements)

References 8 publications

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“…In a previous work we proposed a real-time strategy for a heavy series HEV based on the optimal control over standard city bus driving cycles [9]. Control of series HEVs has also been treated in [10]- [13], but none of them adopt the approach of this work.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Control of Series HEVs Including Resistive Losses and Varying Engine Efficiency

Neuman¹,

Wahlberg²,

Folkesson³

2009

SAE Technical Paper Series

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A model of a series HEV (Hybrid Electric Vehicle) including resistive losses in the energy storage and varying engine and generator efficiency is presented. The purpose is to study how system properties affect the optimal control of series HEVs. We show that there is an inherent trade-off in the control of such a system, based on the characteristics of the efficiency curve of the EGU (Engine and Generator Unit) together with the energy storage internal resistance, capacitance and energy level. The relation between these properties determines the optimal control of the EGU, and this is thus the mechanism behind all optimal control problems using a similar model setup. We illustrate our reasoning using deterministic dynamic programming where system properties are varied and the optimal control is studied.

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Section: Introductionmentioning

confidence: 99%

Modelling and Control of Series HEVs Including Resistive Losses and Varying Engine Efficiency

Neuman¹,

Wahlberg²,

Folkesson³

2009

SAE Technical Paper Series

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“…Konev et al [100] proposed another interesting power management control algorithm aiming at ensuring gradual operation of the engine-generator unit along the steady-state optimal operating points. In the proposed approach, HEV operation is modeled as a random process.…”

Section: B Offline Power Management Control Algorithmsmentioning

confidence: 99%

Supervisory Power Management Control Algorithms for Hybrid Electric Vehicles: A Survey

Malikopoulos

2014

IEEE Trans. Intell. Transport. Syst.

196

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The growing necessity for environmentally benign hybrid propulsion systems has led to the development of advanced power management control algorithms to maximize fuel economy and minimize pollutant emissions. This paper surveys the control algorithms for hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) that have been reported in the literature to date. The exposition ranges from parallel, series, and power split HEVs and PHEVs and includes a classification of the algorithms in terms of their implementation and the chronological order of their appearance. Remaining challenges and potential future research directions are also discussed.Index Terms-Hybrid electric vehicles (HEVs), plug-in HEVs (PHEVs), supervisory power management control algorithms.

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“…Pisu and Rizzoni [8] developed an equivalent consumption minimization strategy (ECMS) with the aim to optimize the energy management for a series hybrid electric heavy duty truck with two energy storage systems, i.e., battery and ultracapacitor. Konev, Lezhnev, and Kolmanovsky [9] implemented a control strategy for a series HEV that ensured gradual operation of the engine-generator unit along the steady-state optimal operating points. In the proposed approach, the HEV operation was modeled as a random process.…”

Section: Introductionmentioning

confidence: 99%

Stochastic optimal control for series hybrid electric vehicles

Malikopoulos

2013

2013 American Control Conference

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Increasing demand for improving fuel economy and reducing emissions has stimulated significant research and investment in hybrid propulsion systems. In this paper, we address the problem of optimizing online the supervisory control in a series hybrid configuration by modeling its operation as a controlled Markov chain using the average cost criterion. We treat the stochastic optimal control problem as a dual constrained optimization problem. We show that the control policy that yields higher probability distribution to the states with low cost and lower probability distribution to the states with high cost is an optimal control policy, defined as an equilibrium control policy. We demonstrate the effectiveness of the efficiency of the proposed controller in a series hybrid configuration and compare it with a thermostat-type controller.

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Control Strategy Optimization for a Series Hybrid Vehicle

Cited by 34 publications

References 8 publications

Modelling and Control of Series HEVs Including Resistive Losses and Varying Engine Efficiency

Modelling and Control of Series HEVs Including Resistive Losses and Varying Engine Efficiency

Supervisory Power Management Control Algorithms for Hybrid Electric Vehicles: A Survey

Stochastic optimal control for series hybrid electric vehicles

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