Suspension Control Research Articles

Neural Network-Interacted Robust Coordinated Control of Full-Vehicle Active Air Suspension With Uncertainties and Time Delays

Neural Network-Interacted Robust Coordinated Control of Full-Vehicle Active Air Suspension With Uncertainties and Time Delays

Cooperative Control of Active Suspension and FourWheel Steering for Intelligent Electric Vehicles with Corner Module Structure on Severe Roads

Cooperative Control of Active Suspension and FourWheel Steering for Intelligent Electric Vehicles with Corner Module Structure on Severe Roads

Turn Compensation Control Development and Analysis for a Self-Propelled Sprayer Chassis Suspension System

Highlights An Experimental sprayer chassis suspension control system was developed and evaluated in headland turns. Turning evaluation performance metrics and methods were conceptualized in the context of sprayers. The Experimental chassis suspension system showed stability and comfort increases during aggressive turns. Boom stability improved significantly after completion of the turn for the Experimental suspension system. Abstract. A challenging economic, environmental, and regulatory landscape causes the need for efficient agricultural machinery. The performance of self-propelled sprayers depends on their ability to deposit chemicals accurately and efficiently, and increased machine sizes and faster driving speeds require consideration for sprayer chassis stability. One method of improving this stability is using variable damping elements in the sprayer chassis suspension system. In this work, an Experimental sprayer chassis suspension system that implemented turning event detection and variable damping control was developed for headland turning events. The Experimental chassis suspension system was tested for a constant speed headland turn maneuver at 10 to 25 m turn radii. The performance of the Experimental system was quantified in terms of operator comfort and operator health, chassis roll and roll rate amplitudes, and boom height sensor standard deviation, and this performance was compared to a Baseline sprayer suspension configuration. From the data collected, the Experimental suspension system improved chassis roll and roll rate stability by 30% to 40% for the entry portion of the turning event regardless of turn radius while also showing a 5% increase in ride quality. The need for tuning the damping level to the chassis yaw rate was identified from decreased comfort performance metrics at larger turn radii. Boom height stability improved significantly for Experimental suspension configurations, particularly after the turning event, showing an 8% to 21% improvement in boom height standard deviation. Further exploration of control parameters and their effects outside turning events should be conducted to ensure optimal control law settings based on machine configurations. Keywords: Chassis suspension, Control, Performance, Self-propelled sprayer, Stability, Turn event, Variable damping.

Single-Phase Suspension Control of Bearingless Switched Reluctance Motor

Single-Phase Suspension Control of Bearingless Switched Reluctance Motor

Basic study on vertical vibrations suppression in railway vehicle carbody by secondary suspension control using bogie vertical vibration velocity

Basic study on vertical vibrations suppression in railway vehicle carbody by secondary suspension control using bogie vertical vibration velocity

Adaptive PPC-Based SMC of Axial Active Suspension Control With Passive Pitching Suppression for Maglev Wind Yaw System

Adaptive PPC-Based SMC of Axial Active Suspension Control With Passive Pitching Suppression for Maglev Wind Yaw System

In vitro encapsulation and expansion of T and CAR-T cells using 3D synthetic thermo-responsive matrices.

Suspension cell culture and rigid commercial substrates are the most common methods to clinically manufacture therapeutic CAR-T cells ex vivo. However, suspension culture and nano/micro-scale commercial substrates poorly mimic the microenvironment where T cells naturally develop, leading to profound impacts on cell proliferation and phenotype. To overcome this major challenge, macro-scale substrates can be used to emulate that environment with higher precision. This work employed a biocompatible thermo-responsive material with tailored mechanical properties as a potential synthetic macro-scale scaffold to support T cell encapsulation and culture. Cell viability, expansion, and phenotype changes were assessed to study the effect of two thermo-responsive hydrogel materials with stiffnesses of 0.5 and 17 kPa. Encapsulated Pan-T and CAR-T cells were able to grow and physically behave similar to the suspension control. Furthermore, matrix stiffness influenced T cell behavior. In the softer polymer, T cells had higher activation, differentiation, and maturation after encapsulation obtaining significant cell numbers. Even when terpolymer encapsulation affected the CAR-T cell viability and expansion, CAR T cells expressed favorable phenotypical profiles, which was supported with cytokines and lactate production. These results confirmed the biocompatibility of the thermo-responsive hydrogels and their feasibility as a promising 3D macro-scale scaffold for in vitro T cell expansion that could potentially be used for cell manufacturing process.

Research on active suspension control based on safety constraint reinforcement learning

Research on active suspension control based on safety constraint reinforcement learning

Advancing Active Suspension Control with TD3-PSC: Integrating Physical Safety Constraints into Deep Reinforcement Learning

Advancing Active Suspension Control with TD3-PSC: Integrating Physical Safety Constraints into Deep Reinforcement Learning

Road profile estimation based on the second generation CRONE control

The objective of this paper is to present a new design method for an unknown input estimator with a closed-loop structure. A frequency domain approach is carried out using a model-based design method and a loop-shaping technique. The loop-shaping approach used to the estimator design is usually applied in the context of control system design. More precisely, it is the second generation CRONE system design methodology that is used. This method is applied to the estimation of a speed bump by using one of the sensors initially intended for suspension control. Note that the noise measurement used in the simulation is recorded from on-board sensors used to control the piloted suspension of a DS7 Crossback. The time responses of the estimator, obtained with a non-linear quarter-car simulator, illustrate the very good results obtained.

Assessment of in Vivo Performance of Lipid-Based Formulations: Correlation between in Vitro Drug Release Profiles and in Vivo Absorption Rate Profiles.

The purpose of this study was to assess the in vivo absorption enhancement effects of lipid-based formulations (LBFs) through in vitro release studies. The type IIIA-MC (medium-chain) and type IIIA-LC (long-chain) formulations containing a Biopharmaceutics Classification System (BCS) Class II drug (dipyridamole or ketoconazole) were used as model LBFs. The type IIIA-MC formulation, but not the type IIIA-LC formulation, showed a higher initial absorption rate than the control suspension for both model drugs in rats. An in vitro side-by-side chamber system coupled with a lipid digestion model was used to measure free drugs, available for intestinal absorption, that are released from a model LBF. The profiles of free drug concentration on the donor side were determined by calculating the ratio of permeation rate (LBF/suspension) at every sampling interval. The in vitro free drug concentration was immediately supersaturated when the digestion of type IIIA-MC formulation was initiated for both drugs, which would cause the initially high absorption rate in rats. In contrast, the free concentration of the type IIIA-LC formulation became lower than the equilibrium solubility over time for both drugs. Overall, the profiles of in vitro free concentrations were consistent with those of in vivo absorption rates for both drugs and all LBFs. These findings would help predict the in vivo performance and establish an in vitro-in vivo correlation (IVIVC) of LBFs.

Combined Light and Thermal Stimulation of Bone Marrow Stem Cells.

Introduction: The purpose of this study is to achieve a significant increase in the proliferative activity of mesenchymal stem cells (MSCs) of the bone marrow (BM) at early passages after laser exposure to a suspension of these cells and to estimate the effect of light and heat components of laser radiation on the proliferation of BM MSCs. Methods: The studies were performed on rats BM MSCs. MSC suspension was placed into the wells and heated by using laser radiation (980 nm wavelength) or a water bath at 70 °C providing similar temperature dynamics. The studies were carried out in 3 comparison groups: (1) control suspension of MSCs, which was not subjected to heating in a water bath or laser exposure; (2) MSC suspension, which was heated for in a water bath; and (3) suspension of MSCs, which was subjected to laser exposure. The exposure times for the 2nd and 3rd experimental groups were 10- 50 seconds. Results: Under optimal parameters of laser action on the suspension of BM MSCs, a six-fold increase in the number of BM MSCs colonies was registered compared to the control. The role of the light and heat components of laser exposure to MSCs was determined by comparable heating of a suspension of BM MSCs in a water bath, at which only a twofold increase in the number of colonies was maximally obtained. Conclusion: The increase in the MSC proliferation activity occurs due to their Thermo-Photobiomodulation. The result obtained is important for practical use in cell transplantation in the treatment of traumatic injuries of bone, cartilage, and tendon tissues when a rapid and multiple increase in the initial number of autologous BM MSCs is required.

Semi-active control for the seat car suspension system using MR elastomer isolator

The suspension system for the car seat is an important part of the vehicle that helps to increase comfort and reduce fatigue. The study of suspension systems using magnetorheological elastomer (MRE) has attracted researchers in recent years. MRE is an elastomer material such as rubber. The modulus of the material can change when a magnetic field is applied. In this study, an MRE-based isolator is first developed for a seat car suspension system. The characteristics of the isolator are investigated under the strength of the magnetic field. Based on Lyapunov theory and constraint force, the semi-active controller is then designed. Numerical simulations for the car seat dynamics system show that the developed isolator can reduce vibrations more when compared with the passive approach in the case of bump and random excitations. The results show significant potential for its application in vehicle seat vibration control.

Removal of polypropylene nanoplastics from aqueous solution by biochar derived from Date palm fibers: Kinetics and isotherms studies

In this work, activated carbon (AC) derived from powder of date palm fibers (DPF) was examined as an adsorbent for removing polypropylene nanoplastics (PPNPs) from aqueous solutions. The adsorbent was characterized using XRD, FT-IR, and SEM analyses. Affecting parameters on removal efficiency in a batch reactor, such as contact time, concentration of PPNPs and amount of adsorbent, were evaluated and optimized. Equilibrium and kinetic studies are performed to understand adsorption mechanisms. In the batch system, 30 mL of polypropylene suspension (5-40 mgL-1) was added to Erlenmeyer flask. First, different amounts of AC adsorbent were added to the container, then microplastic was added to the reactor. The mixture was shaken on a shaker for four hours at 25oC. The flask was removed from the shaker, the concentration of PPNPs in the supernatant was measured, and a settling time of 30 min was obtained. A control suspension system without PPNPs nanoplastics (with biochar and without PPNPs) was also performed to evaluate carbon particle interference by turbidity measurements. Our results showed that kinetic data were consistent with the pseudo-second-order kinetic model. Equilibrium data for the adsorption of PPNPs on biochar represented by the Langmuir isotherm model is better than the Freundlich isotherm model.

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables. The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets. For this purpose, a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities. Then, an asynchronous fuzzy sampled-data controller, featuring distinct premise variables from the active suspension system, is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership. Furthermore, novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous H2 and H∞ performance requirements. Finally, the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.

Retracted: Finite Element Structure Analysis of Automobile Suspension Control Arm Based on Neural Network Control

Retracted: Finite Element Structure Analysis of Automobile Suspension Control Arm Based on Neural Network Control

Analysis of damping multi-mode switching control of semi-active suspension based on digital controlled hydraulic cylinders group

In order to improve the ride comfort of vehicle suspension, this article proposes a damping multi-mode semi-active suspension system and its control method. The semi-active suspension takes a hydraulic electromagnetic shock absorber based on a digital controlled hydraulic cylinders group as the core, and realizes the switching of multiple damping modes by controlling the on-off statuses of three groups of switch solenoid valves, thus making the semi-active suspension have the characteristics of damping multi-mode adjustable. The damping characteristics corresponding to the single damping mode are verified through the prototype bench test of the shock absorber principle. On this basis, the semi-active suspension model of the vehicle is established, and a multi-mode switching control strategy of suspension damping using fuzzy control is designed. The filtered Gaussian white noise is used as the random road excitation for simulation. The simulation results show that compared with the traditional passive suspension and the semi-active suspension based on skyhook control, the damping multi-mode semi-active suspension based on the digital controlled hydraulic cylinders group can realize the switching of multiple damping modes, have good damping performance, and help to improve the vehicle ride comfortable capability.

Ride comfort oriented integrated design of preview active suspension control and longitudinal velocity planning

Aiming for further improvement in ride comfort, a novel integrated system combining preview active suspension control with longitudinal velocity planning based on road height information is proposed. From the suspension control side, the presented semi-EMPC (Explicit Model Predictive Control)-based controller, which is augmented with preview road information, can make up for the shortcomings of traditional implicit MPC and explicit MPC, and achieve a balance between computational burden and memory usage, thus enhancing the practicality of implementing preview suspension in real-world applications. Adopting dynamic programming and quadratic programming algorithms, a longitudinal velocity planning method based on preview information is provided to overcome the vibration that cannot be effectively suppressed by single suspension control, thus expanding the dimension of ride comfort improvement from the original vertical dimension alone to both longitudinal and vertical dimensions. Throughout the design process, the transformation of pavement information among spatial, time, and frequency domains has been regarded as a bridge to combine two systems, thus handling the complex coupling between above two highly interdependent systems. Experiments in the Quanser active suspension plant have been conducted to verify the superiority of semi-EMPC with preview. The integrated approach is simulated in Carsim and shows a significant improvement over single suspension control.

Enhancing vehicle ride comfort through deep reinforcement learning with expert-guided soft-hard constraints and system characteristic considerations

Currently, the research on controlling vehicle ride comfort primarily revolves around utilizing traditional algorithms for active or semi-active control of suspension systems. However, these methods often lack adaptability and necessitate a substantial allocation of human and material resources for system calibration and parameter tuning. With the advancement of cutting-edge computational methods, such as artificial intelligence (AI), being applied in engineering, new opportunities have arisen to tackle knowledge-intensive tasks like suspension control. This study aims to enhance vehicle ride comfort by proposing an active suspension control method that integrates deep reinforcement learning (DRL) while considering system characteristics. Firstly, we construct a Twin Delayed Deep Deterministic Policy Gradient (TD3) architecture to systematically explore control policies. Secondly, we propose an expert-guided soft-hard constraints model (TD3-SH) that synergistically incorporates multi-scale information such as displacement, velocity, acceleration, and control force. Additionally, in practical engineering applications, we introduce action delay mechanisms and hard constraint modules to address time delay and actuator dynamic constraints, thereby alleviating the challenges associated with subsequent parameter adjustments and other knowledge-intensive tasks. Finally, simulations demonstrate the effective mitigation of body vibrations in the low-frequency range and the subsequent improvement of ride comfort by TD3-SH. In comparison to the deep deterministic policy gradient (DDPG), TD3, and model predictive control (MPC) baselines, the proposed method showcases control performance improvements of 54.8%, 35.5%, and 18.3%, respectively. Moreover, the method exhibits ride comfort optimization exceeding 85% across diverse road conditions, showcasing its exceptional generalization and adaptive capacity. Furthermore, the optimization amount exceeding 58% can be sustained despite the constraints of time delay and actuator dynamics. Evidently, the proposed algorithm holds significant potential for engineering applications and is uniquely suited for complex tasks in the vehicle industry characterized by high uncertainty.

Research on robust fault-tolerant control of the controllable suspension based on knowledge-data fusion driven

For the robust fault-tolerant control of the controllable suspension system, a control strategy driven by knowledge-data fusion is proposed. Firstly, the boundary fuzziness between perturbation type uncertainty and gain type fault is analyzed, and then a data-driven method is introduced to avoid the state estimation of system uncertainty and fault. The proximal policy optimization algorithm in reinforcement learning is selected to construct a “data control law”, to deal with uncertainty and fault. On the other hand, based on the classical sky-hook control, the “knowledge control law” for system performance optimization is designed, taking into account the nonlinear and non-stationary characteristics of the system. Furthermore, the dependency between robust fault tolerance and performance optimization control is revealed, and the two control laws are fused by numerical multiplication, to realize the performance matching optimization control of robust fault tolerance of controllable suspension system driven by knowledge-data fusion. Finally, the effectiveness and feasibility of the proposed method are verified by the simulation and real-time experiment of non-stationary excitation and near-stationary excitation under the combination of uncertainty and fault.