AI Article Synopsis
- The efficiency of energy use in autonomous electric vehicles is significantly influenced by their longitudinal motion control, which is limited by driving conditions.
- The article introduces a new method called Energy-Saving Optimization and Control (ESOC) that takes driving constraints into account to enhance energy efficiency.
- ESOC involves optimizing the operation points of the powertrain and has shown through experiments that it achieves better energy consumption results compared to existing techniques.
Article Abstract
The energy utilization efficiency of autonomous electric vehicles is seriously affected by the longitudinal motion control performance. However, the longitudinal motion control is constrained by the driving scene. This article proposes an energy-saving optimization and control (ESOC) method to improve the energy utilization efficiency of autonomous electric vehicles. In ESOC, the constraints from the driving scene are thoroughly considered, and the autonomous driving scene constraints are mapped to the vehicle dynamics and control domain. On this basis, the efficiency self-searching method and the multiconstraint energy-saving control strategy are designed. The main ideology of the proposed ESOC is that the energy utilization efficiency of an autonomous electric vehicle can be improved by optimizing and controlling the operation point distribution of the powertrain efficiency. The experimental results demonstrate that the operation point distribution of the autonomous electric vehicle's powertrain efficiency can be well optimized by the proposed ESOC, and the energy consumption results indicate that the proposed ESOC outperforms the state-of-the-art methods.
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| http://dx.doi.org/10.1109/TCYB.2021.3069674 | DOI Listing |
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