Browse Topic: Active suspension systems
The automotive industry is rapidly evolving with technologies such as vehicle electrification, autonomous driving, Advanced Driver Assistance Systems (ADAS), and active suspension systems. Testing and validating these technologies under India’s diverse and complex road conditions is a major challenge. Physical testing alone is often impractical due to variability in road surfaces, traffic patterns, and environmental conditions, as well as safety constraints. Virtual testing using high-fidelity digital twins of road corridors offers an effective solution for replicating real-world conditions in a controlled environment. This paper highlights the representation of Indian road corridors as digital twins in ASAM OpenDRIVE and OpenCRG formats, emphasizing the critical elements required for realistic simulation of vehicle, tire, and ADAS performance. The digital twin incorporates detailed 3D road profiles (X-Y-Z coordinates), capturing the geometry and surface variations of Indian roads. The
Active suspensions can alter the dynamic behavior of a vehicle in real time to respond optimally to any given operating scenario. Today’s active suspension technologies such as hydraulics, rotary electromagnetics, and linear electromagnetics do offer performance gains but these gains are outweighed by important disadvantages including high power consumption, low quality of force, and high costs and weights. Controlled slippage magnetorheological (MR) actuators are an emerging alternative actuation technology that is light, compact, power dense, and produces a high-quality force, making it ideal for active suspension applications. This article conducts an in-depth experimental assessment of the potential of MR actuators to increase vehicle ride comfort quality when used as active suspensions. Four high power MR actuators are installed on a BMW 330Ci and tests are performed on a closed road. Results show that with an impedance controller, comfort is increased by 67% at 65 km/h and by 61
The objective of the present article is to design a nonlinear passive suspension system for an automobile subjected to random road excitation which generates a performance as close to a fully active suspension system as possible. Linear Quadratic Regulator (LQR) control is used to synthesize an active suspension system. The control forces corresponding to the nonlinear passive suspension and the active suspension are equated, and the parameters are optimized as the performance error between the two systems is reduced. The nonlinear equations of motion are reduced to equivalent linear equations, where the system states are a function of the vehicle response statistics, by using the equivalent linearization method. The performance of the optimized nonlinear model and the linear model are compared with the performance of the LQR control active suspension system. The nonlinear model performs better than the linear system with chosen parameters. The optimized system achieves almost an equal
The vehicle performance is examined based on its specific performance indices. These specific performance indices include stability, ride comfort, steering ability, etc. The vehicle ride comfort is an important factor of vehicle quality and receiving large attention. The majority of previous investigations are focused on vertical vibration analysis of the sprung mass of the vehicle subjected to vertical excitations from the road surface. This study evaluates the ride characteristics of a coupled vertical-lateral 13 degrees of freedom (DoF) full-car model of a light passenger four-wheel vehicle developed with the Lagrangian method. The random vertical and lateral undulations of the road surface have been accounted for in the analysis and represented by the Power Spectral Density (PSD) function. The vehicle ride is assessed based on the International Organization for Standardization (ISO) 2631-1 annexure and the vehicle overall ride index is determined. The vehicle’s vertical-lateral
Ride comfort assessment is undoubtedly related to the interaction between the vehicle tires and the road surface. Indeed, the road profile represents the typical input for tire vertical load estimation in durability analysis and for active/semi-active suspension controller design. However, the road profile evaluation through direct experimental measurements involves long test time and excessive cost required by professional instrumentations to detect the road irregularities with sufficient accuracy. An alternative is shifting attention towards efficient and robust algorithms for indirect road profile evaluation. The object of this work aims at providing road profile estimation starting from vehicle dynamics measurements, through accessible and traditional sensors, with the application of a linear Kalman filter algorithm. The filter is designed and tuned by considering the pitch/bounce half-car models for the prediction phase and by measuring vertical accelerations and angular speeds
The article examines quarter-car dynamics with the possible separation of its tire from the road. A set of nondimensionalized differential equations has been proposed to minimize the involved parameters. Time and frequency response investigation of the system has been analyzed insightfully considering tire-road separation. To measure the separation of the tire, a time fraction index is defined, indicating the fraction of separation time in a cycle at steady-state conditions. Minimizing the index is assumed as the objective of the optimized system. An actuator is applied to the vehicle suspension in parallel with the mainspring and damper of the suspension. Particle Swarm Optimization (PSO) is used to properly tune a Proportional-Integral-Derivative (PID) controller for the active suspension system excited by a harmonic excitation. To verify the effectiveness of the control proposed, the controlled result compared with a passive suspension system illustrates the design, achieving a more
1 Rear wheel drive vehicles have a long driveline using a propeller shaft with two universal joints. Consequently, in this design usage of universal joints within vehicle driveline is inevitable. However, the angularity of the driveshaft resulting from vertical oscillations of the rear axle causes many torsional and bending fluctuations of the driveline. Unfortunately, most of the previously published research work in this area assume the propeller inclination angle is constant under all operating conditions. As a matter of fact, this assumption is not accurate due to the vehicle body attitudes either in pitch or bounce motions. Where the vehicle vibration due to the suspension flexibility, either passive or active type, exists. Moreover, the relative motion between the body and the wheel make this virtualization is so far from the realty in real ground vehicles In this research work, the hydro-pneumatic limited bandwidth active suspension system with wheelbase preview control is
The main objective of this work is to enhance the occupant ride comfort. Ride comfort is quantified in terms of measuring distinct accelerations like sprung mass, seat and occupant head. For this theoretical evaluation, a 7- degrees of freedom (DOF) human-vehicle-road model was established and the system investigation was limited to vertical motion. Besides, this work also focused to guarantee other vehicle performance indices like suspension working space and tire deflection. A proportional-integral-derivative (PID) controller was introduced in the vehicle model and optimized with the aid of the genetic algorithm (GA). Actuator dynamics is incorporated into the system. The objective function for PID optimization was carried out using root mean square error (RMSE) concept. The severity of various suspension indices and biomechanics responses of the developed model under proposed approach were theoretically analyzed using various road profiles and compared with conventional passive
Advanced passenger vehicles are complex dynamic systems that are equipped with several actuators, possibly including differential braking, active steering, and semi-active or active suspensions. The simultaneous use of several actuators for integrated vehicle motion control has been a topic of great interest in literature. To facilitate this, a technique known as control allocation (CA) has been employed. CA is a technique that enables the coordination of various actuators of a system. One of the main challenges in the study of CA has been the representation of actuator dynamics in the optimal CA problem (OCAP). Using model predictive control allocation (MPCA), this problem has been addressed. Furthermore, the actual dynamics of actuators may vary over the lifespan of the system due to factors such as wear, lack of maintenance, etc. Therefore, it is further required to compensate for any mismatches between the actual actuator parameters and those used in the OCAP. This is done by
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