25 research outputs found
Fault Tolerant Strategy for Semi-Active Suspensions with LPV Accommodation
International audienceAbstract--A novel fault tolerant strategy to compensate multiplicative actuator faults (damper oil leakages) in a semiactive suspension system is proposed. The compensation of the lack of damping force caused by a faulty damper is carried on by the remainder three healthy semi-active dampers. Once a faulty damper is detected and isolated by a Fault Detection and Isolation strategy based on parity-space, an estimator is activated to compute the missing damping force to compensate. In order to fulfill the semi-active damper constraints, the fault accommodation is based on the Linear-Parameter Varying (LPV) control strategy. Thus, each corner has a fault estimator and an LPV controller oriented to comfort and road holding. Simulation results show that the proposed fault tolerant semiactive suspension improves the vehicle comfort up to 60% with respect to a controlled suspension without fault-tolerant strategy and 82% with respect to a passive suspension
Adaptive Road Profile Estimation in Semi-Active Car Suspensions
International audienceThe enhancement of the passengers comfort and their safety are part of the constant concerns for car manufacturers. As a solution, the semi-active damping control systems have emerged to adapt the suspension features, where the road profile is one of the most important factors that determine the automotive vehicle performance. Because direct measurements of the road condition represent expensive solutions and, are susceptible to be contaminated, this paper proposes a novel road profile estimator that offers the essential information (road roughness and its frequency) for the adjustment of the vehicle dynamics by using conventional sensors of cars. Based on the Q-parametrization approach, an adaptive observer estimates the dynamic road signal, posteriorly, a Fourier analysis is used to compute online the road roughness condition and perform an ISO 8608 classification. Experimental results on the rear-left corner of a 1:5 scale vehicle, equipped with Electro-Rheological (ER) dampers, have been used to validate the proposed road profile estimation method. Different ISO road classes evaluate online the performance of the road identification algorithm, whose results show that any road can be identified successfully at least 70% with a false alarm rate lower than 5%; the general accuracy of the road classifier is 95%. A second test with variable vehicle velocity shows the importance of the online frequency estimation to adapt the road estimation algorithm to any driving velocity, in this test the road is correctly estimated 868 of 1,042 m (error of 16.7%). Finally, the adaptability of the parametric road estimator to the semi-activeness property of the ER damper is tested at different damping coefficients
Fault Tolerant Control in a Semi-active Suspension
6 pagesInternational audienceA Fault Tolerant Control System (FTCS) in a Quarter of Vehicle (QoV ) model is proposed. The control law is time-varying using a Linear Parameter-Varying (LPV ) based controller, which includes two scheduling parameters. One parameter for monitoring the nonlinear behavior of the damper, and another for fault accommodation using a reference model obtained by a state observer of the normal operating regime. The QoV model represents a semi-active suspension, including an experimental magneto-rheological damper model. The FTCS is analyzed when the velocity sensor fails abruptly and the QoV model is susceptible to disturbances in the road pro le. Simulation results show the e ectiveness of the FTCS in terms of vehicle comfort, suspension detection and road holding in comparison with a conventional LPV based control system. In the FTCS, the comfort index based on the power spectral density is within the desirable bound (1.8) in all range of frequencies, once the sensor fault has occurred; while, the conventional control system deteriorates the comfort 54 %, specially at low frequencies (0-4 Hz). Additionally, the FTCS improves the road holding and suspension de ection indexes, 33% and 39% respectively, when the fault accommodation is considered
Global Chassis Control System Using Suspension, Steering, and Braking Subsystems
A novel Global Chassis Control (GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation
Fault Tolerant Control with Additive Compensation for Faults in an Automotive Damper
International audienceAbstract--A novel Fault-Tolerant Controller is proposed for an automotive suspension system based on a Quarter of Vehicle (QoV) model. The design is divided in a robust Linear Parameter-Varying controller used to isolate vibrations from external disturbances and in a compensation mechanism used to accommodate actuator faults. The compensation mechanism is based on a robust fault detection and estimation scheme that reconstructs a fault on the semi-active damper; this information is used to reduce the failure effect into the vertical dynamics to achieve good control performances. Validations have been made over a QoV model in CarSimTM. Results show the effectiveness of the faulttolerant semi-active damper versus an uncontrolled damper; the improvement is 50.4% in comfort and 42.4% in road holding, by avoiding biases in the damper deflection
Hardware-in-the-loop Testing of On-Off Controllers in Semi-Active Suspension Systems
International audienceThis paper presents an experimental validation of a proposed Frequency Estimation-Based (FEB) controller for semi-active suspensions by using a Hardware-in-the-Loop (HiL) platform of a Quarter of Vehicle (QoV) model. The FEB approach is compared with three commercial On-Off controllers that have shown good results in comfort and road holding: Sky-Hook (SH), Groud-Hook (GH) and Mix-1-sensor (M1S). The comparison was done under the same experimental tests; the standards ISO-2631 and BS-6841 are used to evaluate the comfort and the Root Mean Square (RMS) index to quantify the road holding. The QoV model belongs to a front-left corner of a pick-up truck; the used experimental Magneto-Rheological (MR) damper is not symmetric and only hast 2 manipulation states. Experimental results show that the FEB controller has the best comfort performance at low frequencies (outperforms the benchmark controllers at 11.2%); while, for road holding, the improvement is slight; however, FEB controller works better for both goals simultaneously. By analyzing the suspension deflection, the FEB controller reduces up to 32.8% of motion respect to the GH controller. Additionally, the manipulation of the SH and GH controllers have several changes of actuation that do not allow the stabilization of the force in its desirable value; while FEB controller has a soft actuation defined on bandwidths
Fault detection and diagnosis in a heat exchanger using dynamic principal component analysis and diagnostic observers
A Mathematical Model of Average Dynamics in a Stem Cell Hierarchy Suggests the Combinatorial Targeting of Cancer Stem Cells and Progenitor Cells as a Potential Strategy against Tumor Growth
International audienceThe cancer stem cell hypothesis states that tumors are maintained by a small subpopulation of stem-like cells, often called cancer stem cells (CSCs) or tumor initiating cells. CSCs can self-renew and give rise to more differentiated cells, which comprise the bulk of the tumor. In addition, CSCs are resistant to conventional therapy, which suggests that they are responsible for tumor relapse. This has led researchers to increase efforts to develop directed therapies against CSCs. However, some experiments in mice have shown that the elimination of CSCs might not ensure tumor eradication. This may be due to different events, such as residual CSCs after treatment, the plasticity of cells within the tumor, the presence of different CSCs having their own hierarchy within the same tumor, and the ability of more differentiated cells to maintain the disease, among others. Trying to decipher this complexity may benefit from dissecting the whole in its parts. Here, we hypothesize that tumor relapse after the selective targeting of CSCs may be due to intermediate progenitor (P) cells that can maintain the tumor volume. In order to support the hypothesis, we implemented a mathematical model derived using pseudo-reactions representing the events of each cell subpopulation within the tumor. We aimed to test if a minimal unidirectional hierarchical model consisting of CSCs, P, and terminally differentiated (D) cells could be adjusted to experimental data for selective CSC targeting. We further evaluated therapies ranging from nonselective to specifically directed and combination therapy. We found that selective killing of the CSC compartment has a delaying effect on the overall exponential tumor growth, but was not able to eliminate the disease. We show that therapy that targets both CSCs and intermediate progenitor (P) cells with a sufficient capacity to proliferate and differentiate could represent a more efficient treatment option for tumor depletion. Testing this hypothesis in vivo may allow us to discriminate within the array of possibilities of tumor relapse, and further open the idea of combination therapy against different subpopulations of tumor cells instead of segregating CSCs and bulk tumor cells
Semi active damping force estimation using L P V − H ∞ estimators with different sensing configurations
International audienceSemi-active suspension systems have become a widespread tool to improve the handling and comfort of vehicles. These systems require adjustable dampers as well as supplementary sensing elements. In addition to displacements and accelerations, some of the best performing approaches require knowledge of the semi active damper force. Since this variable can be difficult and expensive to measure, several estimation methods have been proposed. In this article, two Linear-Parameter-Varying (LPV-) filters are developed to estimate the Semi-Active (SA) damper force, considering two different combinations of sensing elements: the first configuration is more expensive, but potentially more accurate and reliable; whereas the second configuration is cheaper and arguably less reliable. Thanks to the use of LPV- theory, both filters are designed to account for the main nonlinear phenomena of SA dampers (i.e. saturation, hysteresis, etc.), as well as being quadratically stable, robust to the road disturbances and optimized to reduce the estimation error in a specified frequency band. Simulations and experimental data are used to assess the proposed estimators as well as a typical inverse-dynamics estimation approach. The results show that while both of the proposed estimators yield a good degree of accuracy, there are indeed fundamental differences depending on the available sensing elements; a conclusion which could be crucial to appropriately define the instrumentation of semi-active suspension systems
Online road profile estimation in automotive vehicles
International audienceThe road profile is one of the most important factors that determine the automotive vehicle performance, specially when it is used to adapt the suspension features. Direct measurements of the road represent expensive solutions and are susceptible to be contaminated. This paper proposes a novel road profile estimation method based on classic vehicle measurements to compute online the road roughness and an ISO 8608 classification; all suspension variables used in the road estimation algorithm are obtained by an H∞ robust observer. The proposed method of road profile estimation is based on the frequency and amplitude estimation of the road irregularities by using a Fourier analysis. Experimental results on the rear-left corner of a 1:5 scale vehicle have been used to validate the proposed road profile estimation method. Different ISO road classes evaluate online the performance of the road identification algorithm, whose results show that any road can be identified at least 70% of success with a false alarm rate lower than 5%; the average error of road identification is 17.46%. A second test with variable vehicle velocity shows the importance of the online frequency estimation to adapt the road estimation algorithm to any driving velocity, in this test the road is correctly estimated 888 of 1,042 m (error of 16.97%)