Robust cooperative game-based control of distributed drive electric vehicles for instability risk mitigation.

Authors

Ji-Wei Feng, Jin-Hao Liang, Pan Liu, Guo-Shun Cai, Ye-Lin He, Guo-Dong Yin, Jian Wu

Published in

Accident; analysis and prevention. Volume 239. Pages 108826. Oct 22, 2026. Epub Oct 22, 2026.

Abstract

In-wheel motor driven distributed drive electric vehicles (DDEVs) extend vehicle dynamic performance boundaries with independent torque control capabilities. However, the deep control coupling between active front steering (AFS) and direct yaw control (DYC) induces functional redundancy and execution conflicts, significantly increasing instability risks, which are a critical precursor to loss-of-control accidents in driver-system shared control scenarios. To address this, this paper constructs a handling stability-oriented cooperative integrated control framework for AFS and DYC. The system parameter uncertainties are handled based on the finite-vertex polytope method, and a compact polytopic robust model is formulated through convex optimization theory. Building upon this modeling, a distributed model predictive control (DMPC)-driven multi-agent dynamic interaction architecture is designed to realize real-time state prediction and cooperative decision optimization. Furthermore, a parallel distributed control mechanism is established by incorporating cooperative game theory to coordinate dynamic weight distribution of actuators, thereby satisfying the modularity and scalability requirements of chassis integrated control. To guarantee system asymptotic stability, terminal input constraints and cost functions are incorporated into a game-theoretic formulation, which is formalized within a linear matrix inequality (LMI) solution framework. An H-infinity robust compensation mechanism is further integrated to suppress external disturbances, which plays a key role in preventing accident-prone instability under system uncertainties. Finally, validation through hardware-in-the-loop (HIL) tests and real vehicle experiments demonstrates the significant effectiveness of the proposed scheme in enhancing lateral stability, reducing accident risk, and improving active safety performance in complex driving scenarios.

PMID:
42913284
Bibliographic data and abstract were imported from PubMed on 24 Oct 2026.

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