Independent Observers-Based Fault Diagnosis for Multiple Sensor Faults of Full-Vehicle Active Suspension Systems With Inaccurate Models

In this paper, an independent observers-based fault diagnosis method is proposed for multiple sensor faults of the full-vehicle active suspension system with an inaccurate model. To address the problem of model uncertainties brought by the linearized full-vehicle suspension model, unmodelled dynamics, parametric uncertainties, and external disturbances are first combined into an integrated uncertain term. Disturbance observers are designed to online track the integrated uncertain terms, whose estimates will be employed to decrease the influence of model uncertainties on fault diagnosis. An independent fault diagnosis observer is designed for each sensor separately, where only the measurement of the matched sensor is taken as the observer input. In this way, each fault diagnosis observer works independently and interactions between measurements of multiple faulty sensors can be decoupled to locate the sensor faults. Anomalies of each sensor are monitored by the fault diagnosis observer in a one-to-one relationship such that fault detection and isolation can be realized at the same time. In particular, the sensitivity and robustness of the fault diagnosis method are improved with the estimates of the integrated uncertain terms injected into the fault diagnosis observers to emulate model uncertainties. Effectiveness of the proposed scheme has been validated via simulation results considering multiple sensor faults occurring at different time or simultaneously. Note to Practitioners—Good reliability of vehicle subsystems is demanded to provide stable rideability and high maneuverability for vehicles, especially for electric vehicles. To guarantee the reliability of the essential components in practice motivates us to focus on the fault diagnosis problems for sensors of vehicle suspension systems. In this paper, considering the possible scenario of multiple sensor faults, an independent observers-based fault diagnosis scheme is designed for full-vehicle suspension systems. By using the proposed method, we can detect the sensor failure and isolate the faulty sensors simultaneously. An independent fault diagnosis observer is built for each sensor with its single sensor measurement taken as the input of the observer. In this way, interactions of the incorrect measurements from the multiple faulty sensors can be removed to avoid interference from these measurement couplings in locating the faulty sensors. Anomalies of each sensor are monitored by its matched fault diagnosis observer in a one-to-one relationship. Different from the existing methods, model uncertainties brought by the linearized full-vehicle suspension model are observed online and their estimates are employed to build the fault diagnosis observers to narrow the gap between the reality and model, and promote the accuracy and effectiveness of the model-based fault diagnosis method. However, incipient sensor faults cannot be effectively diagnosed with our method, which is one drawback of this proposed fault diagnosis scheme. For future work, fault accommodation strategy will be investigated to compensate for the sensor failure and retain satisfactory system performance. Real vehicle experiments will be conducted to test and improve the algorithm, and thus promote the designed method into practical use. The proposed fault diagnosis method for multiple sensor faults can be extended to other mechanical control systems with similar structure of system equations, in addition to vehicle suspension systems.