Chengye Wang | 王成烨

Chengye Wang | 王成烨

he/his

I am currently pursuing my graduate studies at the School of Mechanical Engineering of Beijing Institute of Technology under the supervision of Prof. Yechen Qin

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portfolio

publications

Paper Title Number 4

Published in GitHub Journal of Bugs, 2024

This paper is about fixing template issue #693.

Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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talks

Real-time multidimensional vehicle dynamic stability domain calculation and its application in intelligent vehicles

Published:

Abstrcat:Vehicle stability is fundamental to the safe operation of intelligent vehicles, and real-time, high-accuracy calculation of the stability domain is crucial for maintaining control across the full range of driving conditions. Because the real stability domain is difficult to parameterize accurately and is shaped by multiple driving factors including vehicle-dynamics parameters and environmental conditions, existing approaches fail to capture the multidimensional couplings between time-varying driving inputs and the resulting stability boundaries. Moreover, these methods remain overly conservative owing to algorithmic limitations and cautious design assumptions, thereby restricting dynamic performance in complex scenarios. To address these limitations, this paper introduces a multidimensional vehicle dynamic stability region calculation framework under time-varying driving conditions and apply it into path tracking controller of intelligent vehicle. Sum-of-squares programming (SOSP) is enhanced with iterative shape functions to have a more precise description of the stability domain across discrete operating conditions. A feature analysis of the driving factors including key vehicle parameters and road conditions that influence stability-domain variation is conducted based on the SOSP. A multi-input-multi-output neural network is then used to continuously maps time-dependent driving factors to their stability-domain characteristics. Furthermore, a linear interpolation is adopted to parametrically represent the stability-domain boundary. Verification on a hardware-in-the-loop (HiL) platform demonstrates that the proposed method accurately captures the stability-domain characteristics in time-varying environments subject to multiple factors. Furthermore, the path-tracking controller equipped with the proposed model computes the stability-domain boundary in real time, improves maneuverability by limiting unnecessary interventions, and markedly reduces maximum tracking error.

Coordinated Tracking and Stability Control of Automated Vehicles at the Limits: A Controlled Stability Region Approach

Published:

Abstrcat:Stability criteria serve as the cornerstone of safety for automated vehicles. However, criteria derived from open-loop assumptions often induce conservative interventions, thereby compromising tracking accuracy at handling limits. To address this, this paper presents a Controlled Stability Region (CSR) approach for the coordinated tracking and stability control of automated vehicles. By integrating active control inputs into the nonlinear dynamic system, we quantify a closedloop stability criterion that overcomes the conservatism of open-loop phase plane analysis. Subsequently, a coordinated control strategy (CSR-HMC) is developed, utilizing the CSR as both a dynamic constraint and a weight-adjustment reference to maximize path-tracking potential. Simulations based on a Hardware-in-the-Loop (HiL) platform demonstrate that the CSR-HMC significantly expands the safety boundary compared to open-loop baselines, enabling the vehicle to utilize transient high-maneuverability states and enhance tracking performance in extreme environments.

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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