Analytical Solution for Optimal Stiffness and Damping for Comfort and Road-Holding in the Half Car Model.
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Date
2025
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Publisher
Universidad de Concepción
Abstract
Esta investigación explora el análisis de covarianza en el Modelo de Medio Vehículo (HCM) para derivar parámetros óptimos de suspensión que maximicen, por separado, el confort y la adherencia. Se modelan las irregularidades del camino como perturbaciones de ruido blanco Gaussiano, excluyendo acciones del conductor y eventos discretos.
La investigación comienza reproduciendo técnicas existentes de optimización de la suspensión para el Modelo de Cuarto de Vehículo (QCM, por sus siglas en inglés) utilizando análisis tanto en el dominio del tiempo como en el dominio de la frecuencia. Estos enfoques complementarios producen expresiones analíticas idénticas para parámetros óptimos enfocados en adherencia y confort.
Posteriormente, la investigación extiende estas metodologías analíticas al Modelo de Medio Vehículo de un solo eje, incorporando explícitamente una barra estabilizadora como elemento de interconexión. Esta extensión da como resultado expresiones analíticas para los indicadores de rendimiento y coeficientes óptimos de la suspensión. Las ecuaciones derivadas ilustran explícitamente la influencia de la barra estabilizadora, demostrando que los parámetros de la suspensión deben optimizarse considerando las rotaciones angulares del chasis. Se identifican desviaciones significativas en los parámetros óptimos en comparación con soluciones más simples del QCM, lo que resalta la necesidad de tener en cuenta la dinámica del chasis incluso en escenarios sin barra estabilizadora.
Para el HCM de dos ejes, se adoptan métodos numéricos debido a la complejidad analítica, especialmente por la correlación con desfase de tiempo. Los resultados revelan configuraciones óptimas asimétricas dependientes de la velocidad, incluso en vehículos simétricos. Un análisis de sensibilidad destaca que la estimación precisa de parámetros impacta más que la modelación del desfase.
Este análisis integral supera las limitaciones de modelos simplificados e introduce metodologías avanzadas para optimizar el diseño de suspensiones en términos de confort y adherencia.
This research explores covariance analysis applied to the Half Car Model (Half Car Model (HCM)) to derive optimal suspension parameters that independently maximize comfort and road-holding. By characterizing road irregularities as continuous Gaussian white noise disturbances, and excluding driver inputs and discrete events, the study aims to characterize the system’s response to these excitations. The research begins by reproducing existing suspension optimization techniques for the Quarter Car Model (QCM) using both time-domain and frequency-domain analyses. These complementary approaches yield consistent analytical expressions for optimal parameters targeting road holding and comfort. Subsequently, the investigation extends these analytical methodologies to the single-axle Half Car Model, explicitly incorporating an anti-roll bar as an interconnecting element. This extension results in analytical expressions for performance indicators and optimal suspension parameters. The derived equations explicitly illustrate the anti-roll bar’s influence, demonstrating that suspension parameters must be optimized with consideration of roll dynamics. Notably, significant deviations in optimal parameters are identified compared to simpler QCM solutions, underscoring the necessity of accounting for chassis dynamics even in scenarios without an anti-roll bar. For the two-axle Half Car Model, the complexity of analytically deriving optimal solutions required the adoption of numerical approaches, especially due to correlated and time-delayed road inputs. Optimal suspension configurations are evaluated across various scenarios, revealing asymmetric optimal parameters contingent upon vehicle speed, even in symmetrical vehicle setups. A sensitivity analysis further emphasizes that precise parameter estimation significantly influences suspension performance, potentially surpassing the impact of model complexity. This comprehensive analysis addresses limitations inherent in simplified suspension models and presents advanced methodologies to optimize vehicle suspension systems, offering substantial improvements in design strategies for ride comfort and road holding.
This research explores covariance analysis applied to the Half Car Model (Half Car Model (HCM)) to derive optimal suspension parameters that independently maximize comfort and road-holding. By characterizing road irregularities as continuous Gaussian white noise disturbances, and excluding driver inputs and discrete events, the study aims to characterize the system’s response to these excitations. The research begins by reproducing existing suspension optimization techniques for the Quarter Car Model (QCM) using both time-domain and frequency-domain analyses. These complementary approaches yield consistent analytical expressions for optimal parameters targeting road holding and comfort. Subsequently, the investigation extends these analytical methodologies to the single-axle Half Car Model, explicitly incorporating an anti-roll bar as an interconnecting element. This extension results in analytical expressions for performance indicators and optimal suspension parameters. The derived equations explicitly illustrate the anti-roll bar’s influence, demonstrating that suspension parameters must be optimized with consideration of roll dynamics. Notably, significant deviations in optimal parameters are identified compared to simpler QCM solutions, underscoring the necessity of accounting for chassis dynamics even in scenarios without an anti-roll bar. For the two-axle Half Car Model, the complexity of analytically deriving optimal solutions required the adoption of numerical approaches, especially due to correlated and time-delayed road inputs. Optimal suspension configurations are evaluated across various scenarios, revealing asymmetric optimal parameters contingent upon vehicle speed, even in symmetrical vehicle setups. A sensitivity analysis further emphasizes that precise parameter estimation significantly influences suspension performance, potentially surpassing the impact of model complexity. This comprehensive analysis addresses limitations inherent in simplified suspension models and presents advanced methodologies to optimize vehicle suspension systems, offering substantial improvements in design strategies for ride comfort and road holding.
Description
Tesis presentada para optar al grado de Magíster en Ciencias de la Ingeniería con mención en Ingeniería Mecánica.
Keywords
Automoviles Vibración, Ingeniería mecánica, Damping (Mechanics), Vibration