Comparing Dynamic Programming Optimal Control Strategies for a Series Hybrid Drivetrain

Arvidsson, Rickard; McKelvey, Tomas

doi:10.4271/2017-01-2457

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…X includes, in this case, the battery SOC which is monitored to ensure charge-sustaining HEV operation, to comply with SOC constraints in Equation (11) and to properly evaluate SOC dependent battery parameters such as open-circuit voltage and internal resistance for example. Moreover, real-time tracking of the battery SOC value is performed on-board electrified vehicles as well [35,36].…”

Section: Baseline Dp Formulationmentioning

confidence: 99%

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Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health

Anselma

2022

Energies

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Dynamic programming (DP) is currently the reference optimal energy management approach for hybrid electric vehicles (HEVs). However, several research concerns arise regarding the effective application of DP for optimal HEV control problems which involve a significant number of control variables, state variables and optimization constraints. This paper deals with an optimal control problem for a full parallel P2 HEV with constraints on battery state-of-charge (SOC), battery lifetime in terms of state-of-health (SOH), and smooth driving in terms of the frequencies of internal combustion engine (ICE) activations and gear shifts over time. The DP formulation for the considered HEV control problem is outlined, yet its practical application is demonstrated as unfeasible due to a lack of computational power and memory in current desktop computers. To overcome this drawback, a computationally efficient version of DP is proposed which is named Slope-weighted Rapid Dynamic Programming (SRDP). Computational advantage is achieved by SRDP in considering only the most efficient HEV powertrain operating points rather than the full set of control variable values at each time instant of the drive cycle. A benchmark study simulating various drive cycles demonstrates that the introduced SRDP can achieve compliance with imposed control constraints on battery SOC, battery SOH and smooth driving. At the same time, SRDP can achieve up to 78% computational time saving compared with a baseline DP approach considering the Worldwide Harmonized Light Vehicle Test Procedure (WLTP). On the other hand, the increase in the fuel consumption estimated by SRDP is limited within 3.3% compared with the baseline DP approach if the US06 Supplemental Federal Test Procedure is considered. SRDP could thus be exploited to efficiently explore the large design space associated to HEV powertrains.

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Section: Baseline Dp Formulationmentioning

confidence: 99%

“…These shortcomings have forced the engineers to compromise when implementing DP for optimal HEV control throughout the years. For example, the number of considered control and state variables has been limited, thus introducing important limitations in modeling HEV powertrain operation over time [11].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health

Anselma

2022

Energies

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A Computationally Lightweight Dynamic Programming Formulation for Hybrid Electric Vehicles

Anselma¹,

Rane²,

Biswas³

et al. 2022

SAE Technical Paper Series

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Comparing Dynamic Programming Optimal Control Strategies for a Series Hybrid Drivetrain

Cited by 2 publications

References 13 publications

Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health

Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health

A Computationally Lightweight Dynamic Programming Formulation for Hybrid Electric Vehicles

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