Abstract
The four-wheel-independent-drive electric vehicle (4WID-EV) with typical redundancy characteristics provide a flexible control scheme, including functions such as active front steering (AFS), active rear steering (ARS) and direct yaw moment control (DYC). However, existing work lacks a reasonable method for obtaining the optimal slip ratio based on the 4WID-EV stability control inputs. This is due to the lack of a reasonable method to characterize the lateral stability of the 4WID-EV and the tire force is affected by a variety of parameters, making it difficult to calculate its optimal slip ratio in real time. Thus, this letter investigates methods for characterizing the lateral stability states of 4WID-EV and it incorporates real-time vehicle state monitoring to determine the optimal slip ratio under combined-slip conditions based on effective tire usage rate. Firstly, based on the sideslip angle-yaw rate (β - γ) phase plane analysis, stability boundaries in the front and rear tire slip angle phase plane (αf - αr) are established, which are more suitable for the lateral stability assessment of 4WID-EV under DYC and ARS stability control inputs. Next, an optimal slip ratio calculation method based on lateral stability assessment and effective tire usage rate is proposed to improve the effective utilization of tire force under combined-slip conditions. Finally, based on the back propagation (BP) neural network, an identification model of the optimal slip ratio is established. The test results show that the mean square error (MSE) of the optimal slip ratio under various driving scenarios is 1.1305 × 10−6 and the correlation coefficient (R-value) of the correlation coefficient is 0.9808.
| Original language | English |
|---|---|
| Pages (from-to) | 1098-1105 |
| Number of pages | 8 |
| Journal | IEEE Robotics and Automation Letters |
| Volume | 11 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2026 |
| Externally published | Yes |
Keywords
- Constrained motion planning
- combined-slip conditions
- dynamics
- tire nonlinearities
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