Time-optimal gearshift and energy management strategies for a hybrid electric race car

Duhr, Pol; Christodoulou, Grigorios; Balerna, Camillo; Salazar, Mauro; Cerofolini, Alberto; Onder, Christopher H.

doi:10.1016/j.apenergy.2020.115980

“…Nevertheless, aside from mentioned solutions, there are plenty of applications where the software plays a crucial role. A properly developed control system, e.g., for a gearshift, can enhance the power management for a hybrid V6 unit [12]. Therefore, the optimization of control algorithms and software is of major importance here.…”

Section: Introductionmentioning

confidence: 99%

Energy Optimization of the Continuous-Time Perfect Control Algorithm

Krok

¹

,

Majewski

²

,

Hunek

³

et al. 2022

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In this paper, an attempt at the energy optimization of perfect control systems is performed. The perfect control law is the maximum-speed and maximum-accuracy procedure, which allows us to obtain a reference value on the plant’s output just after a time delay. Based on the continuous-time state-space description, the minimum-error strategy is discussed in the context of possible solutions aiming for the minimization of the control energy. The approach presented within this study is focused on the nonunique matrix inverse-originated so-called degrees of freedom being the core of perfect control scenarios. Thus, in order to obtain the desired energy-saving parameters, a genetic algorithm has been employed during the inverse model control synthesis process. Now, the innovative continuous-time procedure can be applied to a wide range of multivariable plants without any stress caused by technological limitations. Simulation examples made in the MATLAB/Simulink environment have proven the usefulness of the new method shown within the paper. In the extreme case, the energy consumption has been reduced by approximately 80% in comparison with the well-known Moore–Penrose inverse.

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“…The second research line is related to the time-optimal control of racing vehicles such as the hybrid electric F1 car. The majority of prior research in this field optimizes the velocity profile and driving trajectory simultaneously, using nonlinear optimization [16]- [21], or separately solve the energy management problem offline [22]- [25], using convex optimization. Yet these approaches do not capture the impact of the transmission on the motor or engine performance and hence the lap time.…”

Section: Introductionmentioning

confidence: 99%

A Convex Optimization Framework for Minimum Lap Time Design and Control of Electric Race Cars

Borsboom

¹

,

Fahdzyana

²

,

Hofman

³

et al. 2021

IEEE Trans. Veh. Technol.

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published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User

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“…A drawback of simultaneously optimizing the velocity profile and the driving trajectory [2], [3] is, that the problem becomes highly nonlinear, hence an effective simplification consists of condensing the vehicular dynamics and the expert driver's feeling into a maximum speed profile. This way, the resulting time-optimal energy management problem can be solved with a wide variety of methods, such as convex optimization [4], [5], PMP [6], or a combination of approaches [7], [8]. However, these methods lack accurate thermal models on the component-level, or do not explicitly capture the impact of the transmission on the achievable performance.…”

Section: Introductionmentioning

confidence: 99%

Time-optimal Control of Electric Race Cars under Thermal Constraints

Locatello

¹

,

Konda

²

,

Borsboom

³

et al. 2021

2021 European Control Conference (ECC)

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published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User

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Time-optimal gearshift and energy management strategies for a hybrid electric race car

Cited by 36 publications

References 37 publications

Energy Optimization of the Continuous-Time Perfect Control Algorithm

Energy Optimization of the Continuous-Time Perfect Control Algorithm

A Convex Optimization Framework for Minimum Lap Time Design and Control of Electric Race Cars

Time-optimal Control of Electric Race Cars under Thermal Constraints

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