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Implementation and Analyses of an Eco-Driving Algorithm for Different Battery Electric Powertrain Topologies Based on a Split Loss Integration Approach
| Content Provider | MDPI |
|---|---|
| Author | Koch, Alexander Nicoletti, Lorenzo Herrmann, Thomas Lienkamp, Markus |
| Copyright Year | 2022 |
| Description | Eco-driving algorithms optimize the speed profile to reduce the energy consumption of a vehicle. This paper presents an eco-driving algorithm for battery electric powertrains that applies a split loss integration approach to incorporate the component losses. The algorithm consistently uses loss models to overcome the drawbacks of efficiency maps, which cannot represent no-load losses at zero torque. The use of loss models is crucial since the optimal solution includes gliding, during which there are no-load losses. An analysis shows, that state-of-the-art nonlinear programming algorithms cannot represent these no-load losses at zero torque with a small modeling error. To effectively compute the powertrain losses with only a small error in comparison to the measurement data, we introduce a tailored combination of nonlinear inequality constraints that interleave two polynomial fits. This approach can properly represent reality. We parameterize the algorithm and validate the vehicle model used with real-world measurement data. Furthermore, we investigate the influence of the proposed interleaved fits by comparing them to a single continuous high-order polynomial fit and to the state of the art. The algorithm is published open source. |
| Starting Page | 5396 |
| e-ISSN | 19961073 |
| DOI | 10.3390/en15155396 |
| Journal | Energies |
| Issue Number | 15 |
| Volume Number | 15 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-07-26 |
| Access Restriction | Open |
| Subject Keyword | Energies Industrial Engineering Eco-driving Energy-efficient Driving Nonlinear Programming Battery Electric Vehicles Open Source Eco-acc Powertrain Topologies |
| Content Type | Text |
| Resource Type | Article |
