Suspension Performance Research Articles

Dynamics Modeling and Suspension Parameters Optimization of Vehicle System Based on Reduced Multibody System Transfer Matrix Method

This study introduces an innovative vehicle-modeling framework based on the Reduced Multibody System Transfer Matrix Method, incorporating wheel–ground contact and friction to analyze dynamic performance metrics, including vertical acceleration, suspension deflection, and angular acceleration. The model is applied to simulate vehicle behavior at 40 km/h on Class D road conditions. To enhance dynamic characteristics, suspension parameters were optimized using the NSGA-II algorithm. The optimization process achieved significant reductions in vertical acceleration (24.12%), suspension deflection (25.98%), and angular acceleration (4.93%). The Pareto frontier facilitated the selection of a representative solution that balances smoothness, stability, and suspension performance. Frequency, PSD, and RMS analyses were performed under different road conditions and speeds to verify the robustness of the optimization results. The application of the transfer matrix method is extended to vehicle suspension modeling and optimization, offering valuable insights into improving ride comfort and stability. Additionally, it highlights the effectiveness of advanced multi-objective optimization techniques in improving vehicle dynamics and provides a robust methodology for practical applications.

Improving photosynthetic biogas purification via process aeration and nanoparticle supplementation.

This study evaluated the influence of nanoparticles in both suspension and solid format on the performance of a microalgal process devoted to photosynthetic biogas purification. The experimental system consisted of an enclosed tubular photobioreactor coupled to a biogas absorption column through a mixing chamber. The high NH4+ concentration in the inlet mineral medium (530mg N-NH4+ L-1) and the punctual addition of 115mL of nanoparticle suspension to the system caused inhibition of the microalgal-bacterial cultivation. Conversely, cultivation broth aeration (0.5 L min-1 air flowrate) allowed the biomethane production fulfilling the EN 16723 (CH4>90%, CO2<2%). The nanoparticle suspension performance was superior to that of their solid counterparts in terms of CO2 removal efficiency at equivalent nanoparticle dose (77% vs. 49%). However, parameters such as the nanoparticle suspension dosage and biomass concentration in the photobioreactor should be optimized to further improve biomethane quality before its industrial application.

Optimization design and vibration reduction performance analysis of vehicle suspension structure

To improve the vibration reduction performance of vehicle suspension, two kinds of suspension structures (Inerter spring damper, ISD) consisting of inerter, spring and damper are proposed based on electromechanical similarity theory. A single-wheel vehicle system model with I1 and I2 ISD suspension structures is established. Through numerical simulation of single-wheel vehicle system model, the vibration responses of ISD suspension structures I1 and I2 and traditional suspension structures in single-wheel vehicle system are analyzed, and the influence of inertia-capacitance coupling between main and auxiliary parts in ISD suspension structure on vibration reduction performance is discussed. The results show that compared with the traditional suspension structure, the vibration reduction performance of the I1 and I2 ISD suspension structures are improved to a great extent, and the I1 ISD suspension structure is better than the I2 ISD suspension structure. To comprehensively consider the vibration reduction performance of the ISD suspension structure, a compromise optimization method is adopted to determine the inertia-capacitance coupling value.

Road preview method for active suspension based on reinforcement learning

Abstract The pre-identification of impulse road surfaces, such as speed bumps, potholes, and manhole covers, can significantly enhance the performance of active suspension systems. However, existing current identification methods often fail to balance between low cost, high reliability, and precise speed. This study proposes an impulse road surface identification method based on a reinforcement learning network. First, a real dataset of impulse road surfaces was collected, with suspension dynamic responses serving as inputs and random road levels along with impulse road surface features as outputs. This data was used to develop a Random Forest Extreme Gradient Boosting (RF-XGBoost) network to recognize road surface information from vehicle dynamics. Next, a semantic segmentation network was employed to segment road surfaces during intelligent vehicle travel, using road surface information identified by the random forest network as the reward function for reinforcement learning. The reinforcement learning policy was pre-trained using the actual collected data. To validate the effectiveness of the proposed control strategy, a simulation environment was constructed in Prescan, where speed bumps, potholes, and manhole covers of varying heights and sizes were randomly arranged. The reinforcement learning-based road surface identification algorithm was implemented in Simulink, and a co-simulation was conducted with the CarSim vehicle model. The enhanced RF-XGBoost network effectively distinguishes between random and impulse road surfaces, achieving average recognition accuracies of 95.7% for random surfaces and 98.2% for impulse surfaces. During initial training iterations, the RL network exhibited lower accuracy; however, as training progressed, the accuracy for unfamiliar road surface features reached an average of 96.5%, and overall recognition accuracy improved by an average of 9%. The simulation results demonstrate that the proposed reinforcement learning identification method effectively acquires information about the road ahead, shows robustness and generalization, and provides crucial disturbance data for subsequent active suspension control.

Comprehensive Review Comparing the Development and Challenges in the Energy Performance of Pneumatic and Hydropneumatic Suspension Systems

Comprehensive Review Comparing the Development and Challenges in the Energy Performance of Pneumatic and Hydropneumatic Suspension Systems

Synthesis of P(AM/AA/SSS/DMAAC-16) and Studying Its Performance as a Fracturing Thickener in Oilfields.

In order to solve the problems of long dissolution and preparation time, cumbersome preparation, and easy moisture absorption and deterioration during storage or transportation, acrylamide (AM), acrylic acid (AA), sodium p-styrene sulfonate (SSS), and cetyl dimethylallyl ammonium chloride (DMAAC-16) were selected as raw materials, and the emulsion thickener P(AM/AA/SSS), which can be instantly dissolved in water and rapidly thickened, was prepared by the reversed-phase emulsion polymerization method. DMAAC-16, the influence of emulsifier dosage, oil-water ratio, monomer molar ratio, monomer dosage, aqueous pH, initiator dosage, reaction temperature, reaction time, and other factors on the experiment was explored by a single-factor experiment, and the optimal process was determined as follows: the oil-water volume ratio was 0.4, the emulsifier dosage was 7% of the oil phase mass, the initiator dosage was 0.03% of the total mass of the reaction system, the reaction time was 4 h, the reaction temperature was 50 °C, the aqueous pH was 6.5, and the monomer dosage was 30% of the total mass of the reaction system (monomeric molar ratio n(AM):n(AA):n(SSS):n(DMAAC-16) = 79.2:20:0.5:0.3). X-ray diffraction analysis (XRD), infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and scanning electron microscopy analysis were carried out on the polymerization products. At the same time, a series of performance test experiments such as thickening performance, temperature and shear resistance, salt resistance, sand suspension performance, core damage performance, and fracturing fluid flowback fluid reuse were carried out to evaluate the comprehensive effect and efficiency of the synthetic products, and the results show that the P(AM/AA/SSS/DMAAC-16) polymer had excellent solubility and excellent properties such as temperature and shear resistance.

Active Disturbance Rejection Control for an automotive suspension system based on parameter tuning using a fuzzy technique.

Road surface roughness is the cause of vehicle vibration, which is considered a system disturbance. Previous studies on suspension system control often ignore the influence of disturbances while designing the controller, leading to system performance degradation under severe vibration conditions. In this work, we propose a control method to improve active suspension performance that reduces vehicle vibration by eliminating the influence of road disturbances. The proposed method is formed based on the combination of an Active Disturbance Rejection Control (ADRC) technique with control coefficients tuned by a dynamic fuzzy technique formed based on special membership functions called Active Disturbance Rejection Control Based on Fuzzy (ADRCBF). An Extended State Observer (ESO) estimates state variables and disturbances. The performance of the proposed controller is evaluated through the numerical simulation process with three different cases. According to the calculation results, the acceleration and displacement of the sprung mass are significantly reduced when the suspension system is controlled by the proposed technique, compared with the passive suspension system and the active suspension system controlled by a Proportional-Integral-Derivative (PID) technique. In addition, the suspension travel follows the road disturbance with a small error. The error estimated by the ESO does not exceed 3.5% (for sinusoidal and random excitation). In general, system adaptation is ensured under many investigated conditions based on tuning the controller parameters by the soft computing method.

Semi-Active Suspension Design for an In-Wheel-Motor-Driven Electric Vehicle Using a Dynamic Vibration-Absorbing Structure and PID-Controlled Magnetorheological Damper

Abstract: The in-wheel motor (IWM) powertrain layout offers greater design flexibility and higher efficiency of an electric vehicle but has limited commercial success mainly due to the concerns of increased unsprung mass. This paper proposes a semi-active suspension system for in-wheel motors that combines both a dynamic vibration-absorbing structure (DVAS) and a PID-controlled MR damper, in order to achieve optimised comfort, handling and IWM vibration for a small car application. Whilst PID control and DVAS are not entirely new concepts, the usage of both optimisation techniques in a semi-active in-wheel motor suspension has seen limited implementation, which makes the current work novel and significant. The semi-active suspension operating both in passive fail-safe mode and full feedback control was compared to a conventional in-wheel motor passive suspension in terms of sprung mass acceleration, displacement, stator acceleration, tyre deflection and suspension travel for three different road profile inputs using MATLAB/Simulink. The implementation of a PID-controlled MR damper improved road comfort and road holding performance and decreased in-wheel motor vibration over the DVAS passive suspension mainly in terms of a maximum peak amplitude decrease of 40%, 35% and 32% for the sprung mass acceleration, tyre deflection and stator acceleration, respectively. The results are significant since they show that the use of a simple, easily implemented control scheme like PID control was able to significantly improve IWM suspension performance when paired with a DVAS. This study provides further confidence to manufacturers to commercially develop and implement the IWM layout as its major disadvantage can be reasonably addressed using a simple readily available control approach.

Numerical and experimental investigation of vibration of a car chassis and its effect with road gradient on noise and response optimization with factorial design method

This paper delves in to a numerical and experimental investigation of vibration of a car chassis and its effect with road gradient on noise and response optimization. Peak acceleration, peak amplitude as vibration response parameters in vertical motion, internal and pass by noise as a noise response parameters. Vibration parameters obtained numerically by developing a mathematical model of car and equation of motion. Newmark Beta method programmed in MATLAB software used to solve the equation of motion. Experimental investigation of the vibration were carried on a car consist of monocoque chassis, three cylinder engine, Macpherson front suspension and twist beam rear suspension. FFT analyzer and digital sound level meter were used for the data collection. Pass by noise data of vehicle were collected at two locations with gradient 1.15° and 11.31° on state highway (MH SH-44) near Konchi Maharashtra state, India. Comparison between numerical and experimental investigated values of vibration parameters shows minimum error of 0.6035% and average error of 2.81% which validates the car model. Factorial design method was used to optimize the index of response parameters which shows reduction in peak acceleration, peak amplitude, internal noise and pass by noise level by 65.61%, 17.70%, 7.13% and 19.41% respectively. The methodology proposed in this study provides reference to improve the performance of car suspension and passenger comfort.

The occurrence aspects of numerical imbalances and the relationship between temporary suspension and game performance in men’s sevens rugby

The occurrence aspects of numerical imbalances and the relationship between temporary suspension and game performance in men’s sevens rugby

Vehicle active suspension control considering parameter uncertainty and velocity variation

Due to the uncertainty in vehicle model parameters, the control performance of active suspensions often deteriorates, especially under extreme conditions such as high velocities and full loads. To address this challenge, this paper proposes a novel robust finite frequency H ∞ output feedback control strategy based on linear parameter varying (LPV) systems. First, we establish a new LPV model for the half-car active suspension control system, taking into account the uncertainties associated with vehicle velocity and sprung mass. Next, a robust finite frequency H ∞ output feedback controller is designed using a gain scheduling approach, formulated through a set of linear matrix inequalities (LMIs). Finally, simulation results demonstrate that the proposed velocity-dependent robust control strategy significantly reduces the root mean square (RMS) values of vertical acceleration by approximately 21% to 31% under various conditions of sprung mass and vehicle speed compared to traditional control methods.

Comparison of Control Methods for Half-Car Active Suspension System

Suspension systems are of great importance in ensuring stable driving in vehicles and the appropriate reaction of vehicle sub-elements against disturbing inputs. Active suspension systems react quickly to road and driving conditions and positively affect vehicle dynamics and passenger comfort. The main factor in improving active suspension systems' performance is determining the suitable control method against the determined disturbing inputs. This study aims to contribute to the development of vehicle suspension technology by investigating the potential of optimizing the performance of active suspension systems with different control algorithms. In the study, a half-car model with an active suspension system was simulated on three different road profiles: bump-pit, sinusoidal, and ISO-8608. Fuzzy logic, PID, Fuzzy-PID, and MPC control methods are used to control the active suspension system, and their advantages over each other and the passive suspension system are investigated. The effectiveness of the control methods determined on each road profile has been analyzed in the evaluations made regarding vehicle dynamics and passenger comfort. As a result of the study, it is observed that the MPC control algorithm was able to control the active suspension system stably and quickly on all three road profiles with a high success rate. The best results are obtained by the MPC algorithm for bump pit, sinusoidal, and ISO8608 road profiles, and the RMSE values for each road profile are 1.466, 0.047, and 0.449, respectively. The suitable control method minimized vehicle body displacement and pitch angle and improved vehicle stability. In the passenger comfort evaluation, 33.49%, 47.79%, and 12.26% improvements were obtained using the MPC control method on bump-pit, sinusoidal, and ISO-8608 road profiles, respectively.

Evaluation of the unsprung mass effect on ride comfort of in-wheel motor driving vehicles

As an innovative powertrain configuration for electric vehicles, in-wheel motor drive has tremendous potentials. However, the influence of excessive unsprung mass related to the in-wheel motor drive on vehicle performance remains ambiguous or even controversial. This paper tries to address the issue based on a full-vehicle model, taking into consideration different road profiles, body positions and vehicle speeds. A full-vehicle model is established for an in-wheel motor driving vehicle, and a centralized driving vehicle with lighter unsprung mass is taken as the baseline vehicle. Simulation studies are carried out for both vehicle configurations at various speeds on random and bumpy road profiles, respectively. Various observations about the effects of the increased unsprung mass are obtained and clarified, including those mentioned in the literature and some new ones. The results indicate that, for random roads, the increased unsprung mass enlarges the wheel dynamic load and suspension travel, and thus deteriorates the road holding and suspension performances. Interestingly, the effects of the increased unsprung mass on body vertical acceleration vary with body position due to the wheelbase filtering property. Front and rear body accelerations are magnified with the increased unsprung mass at all speeds, whereas the body centroid acceleration exhibits an alternating pattern of increase and decrease throughout the speed range. Moreover, the increased unsprung mass reduces the body roll acceleration at all speeds. For bump roads on the other hand, the increased unsprung mass deteriorates all metrics at low speeds, but improves them at high speeds.

Markov multi-fault tolerance control of intelligent suspension in blind scenes

This paper focuses on insufficient perception in blind scenes and the failures of the actuator and sensor of vehicle suspension. The safe speed is designed and the fault-tolerant strategy based on the observer is designed when the actuator and sensor fail simultaneously. A speed planning strategy to ensure that vehicles operate at a safe speed is proposed. The Markov suspension fault jump model considering the suspension sensor and actuator faults is established. Based on the fault estimation obtained by the fault observer, a fault tolerance control strategy of sensor signal reconstruction and actuator fault compensation is adopted. The measurement index for evaluating fault tolerance effectiveness has been established, and an exploration of fault tolerance control is conducted across various fault levels, to identify the preferred fault tolerance strategies corresponding to different levels of fault tolerance. The simulation results show that the designed speed control strategy can improve vehicle safety by decelerating in advance, the fault observer is capable of accurately estimating the true values of actuator and sensor faults. The simulation and vehicle test results demonstrate that similar suspension performance has been obtained by fault-tolerant control strategy and preferred fault tolerance under different fault tolerance levels compared with normal fault tolerance.

Influence of particle morphology on solar thermal conversion performance and sensible heat storage capacity: A case study of TiO2@Go binary nanofluid

Photothermal catalytic hydrogen production driven by the full spectrum of outdoor solar radiation, represents a highly promising and efficient approach for hydrogen generation. This method is widely anticipated by researchers due to its potential to enhance photon utilization efficiency at the reaction source. However, limited attention has been devoted to the variations in photothermal conversion performance of particle reaction suspensions caused by objective fluctuations of solar irradiation, especially when the morphology of the nanostructure changes, which is a crucial factor for practical applications in hydrogen production. Based on this bottleneck, we prepared the typical photo-responsive TiO2@Go composite with varied dimensions (i.e., nanosphere TiO2@Go, nanorod TiO2@Go, nanosheet TiO2@Go) as research models, and systematically investigated their thermal conversion and sensible heat conversion performance under different working conditions. The results showed that at low nanofluid concentration, nanosphere TiO2@Go and nanosheet TiO2@Go exhibit better sensible heat conversion. As the particle concentration increases, the sensible heat conversion efficiency of all nanofluids decreases. It can also be found that the latent heat conversion efficiency tends to increase with the increase of concentration, but the nanorod TiO2@Go show the opposite, which should be closely related to the uniformity of the particle size in different directions. In addition, for the sensible heat storage properties of nanofluids, smaller particle size and abundant porosity due to particles aggregation were found to be more beneficial for varied shapes. The underlying functional mechanisms were elucidated associated with the analysis of particle structures, interfacial properties, and optical characteristics. We contend that our research could provide valuable insights for the large-scale implementation of solar photothermal hydrogen production and a reasonable selection of photothermal material morphology for outdoor working conditions.

Local Probe Measurements for Designing More Efficient Photocatalyst Systems

Photocatalytic water splitting is one promising route to reducing the cost of H2 production to industrially relevant levels. However, these particle-based systems are currently limited in their solar-to-hydrogen efficiency, requiring further development in photoabsorber and co-catalyst materials that can achieve both high activity and selectivity. One scientific challenge to advancing development of photocatalytic particles is that conventional analytical methods used to assess the performance of particle suspensions or sheets tend to measure the average or ensemble performance of a large population of particles having a distribution of sizes and compositions while often being exposed to both optical and chemical gradients within the reaction vessel. As a result, it is very difficult to uncover the structure-property-performance relationships that can guide rational design of photocatalysts. Local measurements, such as scanning electrochemical microscopy (SECM) and Raman microscopy, provide information at smaller length scales which can aid in understanding structure-property-performance relationships of individual photocatalyst particles as well as interactions between neighboring particles. Additionally, these tools can be utilized with model systems to understand how different phenomena are coupled, as well as with the introduction of selective coatings which are common in the field. As a part of broader efforts within the EFRC Ensembles of Photosynthetic Nanoreactors (EPN), our team is also advancing the use of these local techniques to correlate multiple measurements on identical particle, location or particle systems across of network of microscopists. Here, we explore the usage of Raman and SECM on model photocatalysts within the EPN correlative microscopy network. Extension of these observations to ensemble systems based on multiple particles will additionally be discussed.

The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings.

Inequalities exist in children's educational outcomes-including reading proficiency, school discrimination, and school disciplinary actions-across zip codes with different levels of educational childhood opportunity index (COI). This study examines the interaction between race and educational environment on children's educational outcomes. We hypothesize that race, parental education, and their interaction are associated with perceived school discrimination, which in turn reduces their cognitive, academic, and emotional wellbeing. We also hypothesize that Black children with high socioeconomic status (SES) report high perceived school discrimination in high-COI settings. Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study, which measures a wide range of educational, cognitive, and emotional outcomes. At the same time, the ABCD children are sampled across areas with vast differences in COI rankings, that can be classified into these five categories: very high, high, average, low, and very low educational COIs. Our structural equation models (SEM) tested the additive and interactive effects of race and educational attainment on perceived school discrimination, and the effects of school discrimination on various cognitive abilities (reading proficiency, picture vocabulary, and list sorting working memory), school suspension, as well as depressed mood. Our multi-group SEM assessed how these relationships vary across educational COI levels. Our findings showed that high SES Black children report highest school discrimination in residential areas with highest COIs. This is based on the observation that the interaction between race and parental education on experiences of school discrimination were only significant in areas with highest COI. Across residential areas with different COI levels, students who experienced higher school discrimination had higher suspension, worse depression, and worse cognitive performance. While higher COIs are associated with better academic outcomes, Black-White gaps exist in the role of increased COI through increased racial bias that children perceive. These findings underscore the complexity of educational equity, suggesting that improving COI alone is insufficient for eliminating racial disparities in school experiences. Policies should be in place to reduce school-based discrimination against Black students in high COI settings.

Dual winding slot area allocation ratio effect on torque and suspension performance of BPMSMs

Dual winding slot area allocation ratio effect on torque and suspension performance of BPMSMs

Active suspension using a PID controller with an inerter device

This article is dedicated to a thorough investigation of the behavior of an active suspension system that incorporates the PID controller in a vehicle quarter, adding an inerter component to the system. Through comprehensive analysis of a variety of track profiles, the active suspension system demonstrates its ability to precisely control wheel movements, with the primary aim of improving passenger comfort and vehicle handling. By using the PID controller in conjunction with track sensors, the system is able to continuously evaluate road conditions, identifying the most effective movements to optimize the driving experience. The PID controller, incorporating proportional, integral, and derivative components, plays a fundamental role in minimizing error, integrating corrections, and adjusting response time as needed. The inerter, an innovative mechanical device with two terminals, is introduced to provide inertia without adding mass to the system, utilizing the difference in angular acceleration between the terminals. To validate and compare the performance of the active suspension system with and without the inerter, detailed simulations are conducted using the powerful tools of MATLAB and Simulink. The inclusion of the inerter in the active suspension system, along with the PID controller, aims to enhance the overall effectiveness of the system, even if it results in a slight increase in manufacturing costs. However, the substantial benefits in terms of passenger comfort and vehicle safety fully justify this additional investment. This approach represents a significant advancement in the field of automotive suspension systems, offering an ideal balance between performance, cost, and user satisfaction.

Performance comparison of an Inerter Suspension

Recent enhancements in automotive suspension systems have significantly increased vehicle safety, comfort, and dynamics. The inerter integration is an innovation, improving stability and comfort by dampening vibrations. As a two-terminal inertial element, the inerter creates a resistance force proportional to the relative acceleration between the terminals, quantified by the inertance constant in kilograms (kg). This research investigates the dynamics of a passenger vehicle using a 14 Degrees of Freedom (DOF) vehicle model that includes an inerter, alongside traditional springs and dampers. Comparisons are drawn between this comprehensive model and quarter-model and half-transversal car models. Employing VI-CarRealTime and MATLAB/SIMULINK for simulations, the study seeks to elucidate the enhancements in suspension performance attributable to the inerter across different road conditions.