Energy management strategy to be used in design space exploration for electric powertrain optimization

Vaillant, Moritz; Eckert, Michael; Gauterin, Frank

doi:10.1109/ever.2014.6844026

Cited by 2 publications

(4 citation statements)

References 8 publications

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“…The results using the control strategy st 10 are shown in Figures 18(a) The results obtained for route 2 are presented in Table 7. For route 2 compared to route 1, the best results were achieved using the st V10 vector.…”

Section: Determination Of the Optimal Control Strategymentioning

confidence: 99%

“…the phenomenon of loss can be found in professional literature [10]. The motor torque is transmitted to the drive wheel via the TS transmission.…”

Section: Mathematical Model Of the Vehiclementioning

confidence: 99%

“…For routes 2 and 3, the same as for route 1, the procedure was followed. Optimization strategies have been optimized for all variants of control vector st , st 15 , st 10 .…”

Section: Determination Of the Optimal Control Strategymentioning

confidence: 99%

“…In paper [9], this is demonstrated by the synchronous motor, written in MATLAB and Simplorer. In order to reduce the computational time, the model should be written in a low-level language, e.g., C, as given in [10] and the simulation time can be reduced by up to 20 times compared to a program written in MATLAB's own language.…”

Section: Introductionmentioning

confidence: 99%

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Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars

Targosz

Skarka

Przystałka

2018

Journal of Advanced Transportation

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The article presents a method for optimizing driving strategies aimed at minimizing energy consumption while driving. The method was developed for the needs of an electric powered racing vehicle built for the purposes of the Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. Model-based optimization was used to determine the driving strategy. The numerical model was elaborated in Simulink environment, which includes both the electric vehicle model and the environment, i.e., the race track as well as the vehicle environment and the atmospheric conditions. The vehicle model itself includes vehicle dynamic model, numerical model describing issues concerning resistance of rolling tire, resistance of the propulsion system, aerodynamic phenomena, model of the electric motor, and control system. For the purpose of identifying design and functional features of individual subassemblies and components, numerical and stand tests were carried out. The model itself was tested on the research tracks to tune the model and determine the calculation parameters. The evolutionary algorithms, which are available in the MATLAB Global Optimization Toolbox, were used for optimization. In the race conditions, the model was verified during SEM races in Rotterdam where the race vehicle scored the result consistent with the results of simulation calculations. In the following years, the experience gathered by the team gave us the vice Championship in the SEM 2016 in London.

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Section: Determination Of the Optimal Control Strategymentioning

confidence: 99%

“…the phenomenon of loss can be found in professional literature [10]. The motor torque is transmitted to the drive wheel via the TS transmission.…”

Section: Mathematical Model Of the Vehiclementioning

confidence: 99%

“…For routes 2 and 3, the same as for route 1, the procedure was followed. Optimization strategies have been optimized for all variants of control vector st , st 15 , st 10 .…”

Section: Determination Of the Optimal Control Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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