<p>The intelligent chassis has become a central focus in the development of intelligent vehicles (IVs) in recent years, where the active toe system (ATS) improves the handling stability of IVs by adjusting wheel alignment to effectively coordinate the lateral and longitudinal dynamics. The common ATS suspension design hardly took the impact of active control into consideration on the suspension system design, and coordinating the suspension mechanical design and control design during the design stage will further improve the suspension and vehicle dynamics performance. This paper proposes the hierarchical control-configured design method of the active toe system (HCCD-ATS) to improve the IVs handling and trajectory tracking performance by parallel cooperation between the ATS mechanical subsystem and ATS control subsystem at the design stage. The HCCD-ATS divides the suspension system optimization into an upper system-level optimization and a lower subsystem-level parallel optimization: The upper system-level constructs the optimizer and algorithm, with design variables including the toe actuator installation hardpoints and actuator stroke, active toe control parameters, and toe kinematics characteristic (K-Toe). While the lower subsystem-level constructs ATS subsystems including the suspension physical model, active toe controller and their simulation process, tracks the upper-level variables according to the constraints and obtains evaluations of each subsystem. Besides, the parametric suspension toe kinematics characteristic (K-Toe) is set as shared variables, enabling the interaction between subsystems to transition into system-level and subsystem interactions during the design stage. Then, the control-configured design idea is used to align the toe control margin with K-Toe design domain at the system level by dynamically updating system-level constraints. Simulation tests show that, compared to the traditional sequential design of “mechanical design first followed by control design”, the HCCD-ATS, avoiding the limitation where suspension mechanical optimization, is constrained by subsystem optimization objectives, thereby failing to fully realize the overall system performance, improved the ATS vehicle trajectory tracking performance by an average of 2.55% and reduced the peak yaw rate tracking error by 16.43% during a double-line change at 80 km/h, <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$\mu = 0.85$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>μ</mi> <mo>=</mo> <mn>0.85</mn> </mrow> </math></EquationSource> </InlineEquation>.</p>

Hierarchical Control-Configured Design Method of Active Toe System for Intelligent Vehicles

期刊论文
发表日期：

2026年1月12日

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Xinjie Zhang,
Luhang Wang,
Konghui Guo,
Yang Liu,
Gengrui Jin

摘要

The intelligent chassis has become a central focus in the development of intelligent vehicles (IVs) in recent years, where the active toe system (ATS) improves the handling stability of IVs by adjusting wheel alignment to effectively coordinate the lateral and longitudinal dynamics. The common ATS suspension design hardly took the impact of active control into consideration on the suspension system design, and coordinating the suspension mechanical design and control design during the design stage will further improve the suspension and vehicle dynamics performance. This paper proposes the hierarchical control-configured design method of the active toe system (HCCD-ATS) to improve the IVs handling and trajectory tracking performance by parallel cooperation between the ATS mechanical subsystem and ATS control subsystem at the design stage. The HCCD-ATS divides the suspension system optimization into an upper system-level optimization and a lower subsystem-level parallel optimization: The upper system-level constructs the optimizer and algorithm, with design variables including the toe actuator installation hardpoints and actuator stroke, active toe control parameters, and toe kinematics characteristic (K-Toe). While the lower subsystem-level constructs ATS subsystems including the suspension physical model, active toe controller and their simulation process, tracks the upper-level variables according to the constraints and obtains evaluations of each subsystem. Besides, the parametric suspension toe kinematics characteristic (K-Toe) is set as shared variables, enabling the interaction between subsystems to transition into system-level and subsystem interactions during the design stage. Then, the control-configured design idea is used to align the toe control margin with K-Toe design domain at the system level by dynamically updating system-level constraints. Simulation tests show that, compared to the traditional sequential design of “mechanical design first followed by control design”, the HCCD-ATS, avoiding the limitation where suspension mechanical optimization, is constrained by subsystem optimization objectives, thereby failing to fully realize the overall system performance, improved the ATS vehicle trajectory tracking performance by an average of 2.55% and reduced the peak yaw rate tracking error by 16.43% during a double-line change at 80 km/h, $\mu = 0.85$ $μ = 0.85$ .