A novel active suspension control design method is proposed for attenuating vibrations caused by road disturbance inputs in vehicle suspension systems. For the control algorithm, we propose an intelligent PD controller structure that effectively rejects online estimated disturbances. The main theoretical techniques used in this paper consist of an ultra-local model which replaces the mathematical model of quarter car system and a new algebraic estimator of unknown information. The measurement of only input and output variables of the plant is required for achieving the reference tracking task and the cancellation of unmodeled exogenous and endogenous perturbations such as roughness road variation, unpredictable variation of vehicle speed and load variation. The performance and robustness of the proposed active suspension algorithm are compared with ADRC control and LQR control. Numerical results are provided for showing the improvement of passenger comfort criteria with model-free control.

In order to isolate the propagation of unwanted vibrations to passengers and improve vehicle maneuverability, it is common practice to predict road profile roughness in the scope of active suspension design. An algebraic estimator designed for the estimation of the road profile excitation has been investigated in this study based on vehicle dynamics responses. An approximation of road profile excitation by a piecewise constant function has been proposed using the operational calculus method and the differential algebraic theory. The proposed technique allows for the usage of cheap instrumentation with a small number of sensors and employs a straightforward calibration process. Accurate approximation of the road profile was obtained from the measurement of sprung mass and unsprung mass vertical displacements. The performance and robustness of the proposed algebraic predictor is compared with an augmented Kalman estimator. Numerical results are provided to analyze the effectiveness and the limitations of the proposed algorithm for road profile reconstruction. Furthermore, a comparison with real profile was studied.

Vibration condition monitoring is a non-devastating technique that can be performed to detect tooth cracks propagating in gear systems. This paper proposes to apply a new methodology using time-domain analysis, frequency-domain analysis, and statistical process control charts (SPCC) for gear crack detection of a 10 DOF dynamic model of spiral bevel gear system (SBGS). The gear mesh stiffness effect used in the model has been studied analytically for different levels of crack faults. Adding Gaussian white noise is discussed as the first step to simulating the initial modeling signals of real-world conditions. Second, time-domain signal analysis was performed to identify periodic vibration pulses as failure components and calculate the statistical standard deviation (STD) feature as a fault-sensitive feature. Third, a fast Fourier transform (FFT) to time signals of the variable gear mesh stiffness was applied to determine the gear mesh frequency and sidebands to detect tooth cracks. Fourth, the SPCC was designed using the Shewhart X-bar chart and an exponentially weighted moving average (EWMA) chart based on the STD feature of the healthy gears. Finally, in the testing stage, the control charts are carried out with simulation signals under faulty conditions to detect the different levels of cracks. The results showed that the EWMA chart outperformed the time domain analysis, frequency domain analysis, and Shewhart X-bar chart in detecting all levels of cracks at an early stage.

A novel active suspension control strategy is introduced to improve dynamic response of vehicle suspension systems. The proposed algorithm is a fusion of classical controller design methods together with an online observer and is based on the cancelation of system disturbances. The operational calculus method and the differential algebraic theory are applied to build the observer/compensator that is appended to the classical linear quadratic regulator. An ultra-local model based on linear algebraic rules is presented avoiding the use of a precise mathematical model while guaranteeing the stability of the overall system. Simplicity of implementation, low power demand and significant enhancement of active suspension performance are the observed features of the proposed controller. The numerical simulations illustrate the effectiveness and the robustness against sprung mass variation of the proposed control method compared to proportional–integral–derivative controller, intelligent proportional–derivative controller, linear quadratic regulator and active disturbance rejection—linear quadratic regulator.

A new technique of active control is presented for enhancing the dynamic responses of full car systems with bias to ride comfort performance. A seven degrees of freedom full car model is used, and its performance is evaluated on a bump road and random road. The proposed scheme is a combination between traditional controller design methods with an algebraic estimator of perturbations that will be eliminated online. From the inputs and the outputs signals, the unmodeled phenomenon can be estimated and be subtracted for ensuring the proper functioning of the system. The precise mathematical model of the system is not required for the implementation of the control scheme and is replaced by ultra-local models. Furthermore, the effectiveness of the algebraic estimator of road profile is introduced for applying the excitation sources of the reference generator. The road profiles in front of the vehicle are estimated separately from the rear road profiles. The ride comfort is improved progressively with the novel controller configuration by 83% from the passive case. Further, pitching and rolling fluctuations are reduced by 80% and 85% respectively. The numerical simulations illustrate the effectiveness and the robustness against vehicle body mass deviation and nonlinear actuator saturation of the proposed control method compared to passive and Active Disturbance Rejection Controller based on Input Decoupling Transformation.