Scipediacontent: Scipediacontent moved page Draft Content 137908639 to 238,295kh

2021-03-22T22:46:48Z

Scipediacontent moved page Draft Content 137908639 to 238,295kh

Scipediacontent: Created page with " == Abstract == Energy management systems are used to find a compromise between conflicting goals that can be identified for battery electric vehicles. Typically, these are t..."

2021-03-22T22:45:37Z

Created page with " == Abstract == Energy management systems are used to find a compromise between conflicting goals that can be identified for battery electric vehicles. Typically, these are t..."

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== Abstract ==

Energy management systems are used to find a compromise between conflicting goals that can be identified for battery electric vehicles. Typically, these are the powertrain efficiency, the comfort of the driver, the driving dynamics, and the component aging. This paper introduces an optimization-based holistic energy management system for a battery electric vehicle. The energy management system can adapt the vehicle velocity and the power used for cabin heating, in order to minimize the overall energy consumption, while keeping the total driving time and the cabin temperature within predefined limits. A genetic algorithm is implemented in this paper. The approach is applied to different driving cycles, which are optimized by dividing them into distinctive time frames. This approach is referred to as the sliding window approach. The optimization is conducted with two separate driving cycles, the New European Driving Cycle (NEDC) and a recorded real-world drive. These are analyzed with regard to the aspects relevant to the energy management system, and the optimization results for the two cycles are compared. The results presented in this paper demonstrate the feasibility of the sliding window approach. Moreover, they reveal the differences in fundamental parameters between the NEDC and the recorded drive and how they affect the optimization results. The optimization leads to an overall reduction in energy consumption of <inline-formula> <math display="inline"> <semantics> <mrow> <mn>3.37</mn> <mo>%</mo> </mrow> </semantics> </math> </inline-formula> for the NEDC and <inline-formula> <math display="inline"> <semantics> <mrow> <mn>3.27</mn> <mo>%</mo> </mrow> </semantics> </math> </inline-formula> for the recorded drive, without extending the travel time.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_137908639-beopen1293-6149-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.3390/wevj10020046 http://dx.doi.org/10.3390/wevj10020046] under the license https://creativecommons.org/licenses/by

* [http://dx.doi.org/10.3390/wevj10020046 http://dx.doi.org/10.3390/wevj10020046] under the license http://creativecommons.org/licenses/by/3.0/

* [https://www.mdpi.com/2032-6653/10/2/46/pdf https://www.mdpi.com/2032-6653/10/2/46/pdf] under the license https://creativecommons.org/licenses/by/4.0

* [https://www.mdpi.com/2032-6653/10/2/46 https://www.mdpi.com/2032-6653/10/2/46],
: [https://doaj.org/toc/2032-6653 https://doaj.org/toc/2032-6653] under the license cc-by

* [https://www.mdpi.com/2032-6653/10/2/46/htm https://www.mdpi.com/2032-6653/10/2/46/htm],
: [http://mediatum.ub.tum.de/node?id=1509853 http://mediatum.ub.tum.de/node?id=1509853],
: [https://academic.microsoft.com/#/detail/2952020680 https://academic.microsoft.com/#/detail/2952020680]

* [https://www.mdpi.com/2032-6653/10/2/46/pdf https://www.mdpi.com/2032-6653/10/2/46/pdf],
: [http://dx.doi.org/10.3390/wevj10020046 http://dx.doi.org/10.3390/wevj10020046]

under the license https://creativecommons.org/licenses/by/4.0/

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Scipediacontent: Scipediacontent moved page Draft Content 137908639 to 238,295kh

Scipediacontent: Created page with " == Abstract == Energy management systems are used to find a compromise between conflicting goals that can be identified for battery electric vehicles. Typically, these are t..."