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It is recognized that there is a dearth of studies that provide a comprehensive understanding of vehicle-occupant system dynamics for various road conditions, sitting occupancies and vehicle velocities. In the current work, an in-house-developed 50 degree-of-freedom (DOF) multi-occupant vehicle model is employed to obtain the vehicle and occupant biodynamic responses for various cases of vehicle velocities and road roughness. The model is solved using MATLAB scripts and library functions. Random road profiles of Classes A, B, C and D are generated based on PSDs (Power Spectral Densities) of spatial and angular frequencies given in the manual ISO 8608. A study is then performed on vehicle and occupant dynamic responses for various combinations of sitting occupancies, velocities and road profiles. The results obtained underscore the need for considering sitting occupancies in addition to velocity and road profile for assessment of ride comfort for a vehicle.

Growing consumer expectations continue to fuel further advancements in vehicle ride comfort analysis including development of a comprehensive tool capable of aiding the understanding of ride comfort. To date, most of the work on biodynamic responses of human body in the context of ride comfort mainly concentrates on driver or a designated occupant and therefore leaves the scope for further work on ride comfort analysis covering a larger number of occupants with detailed modeling of their body segments. In the present study, governing equations of a 13-DOF (degrees-of-freedom) lumped parameter model (LPM) of a full car with seats (7-DOF without seats) and a 7-DOF occupant model, a linear version of an earlier non-linear occupant model, are presented. One or more occupant models can be coupled with the vehicle model resulting into a maximum of 48-DOF LPM for a car with five occupants.

Across the automotive industries, objective measurements and subjective assessment of vehicle ride performance are routinely carried out during development as well as validation phase. Objective measurements are receiving increased attention as they are generally believed to offer a higher degree of objectivity and repeatability compared to the subjective assessment alone. Typical industry practices include the acquisition of vehicle-occupant vibrational response on specified road sections, test surfaces on proving grounds or in a controlled input environment such as four-poster test rig. In presented work, a study is performed on the repeatability of vehicle ride performance metrics such as weighted RMS acceleration and frequency responses using the data acquired in repeated trials conducted using three different sports utility vehicles (SUVs) on a sufficiently long designated road section.

Objective metrics for performance evaluation of ride, handling and steering are required to compare, validate and optimize dynamic behavior of vehicles. Some of these objective metrics are recommended and defined by International Organization for Standardization (ISO) and Society of Automotive Engineers (SAE), which involve data processing, statistical analysis and complex mathematical operations on acquired data through simulation or experimental testing. Due to the complexity of operations and volume of data, evaluation is often time consuming and tedious. Process automation using existing tools such as MS Excel, nCode, Siemens LMS, etc. includes several limitations and challenges, which make it cumbersome to implement. This work is about development of a centralized platform for quantification, visualization and comparison of ride, handling and steering performance metrics obtained from testing and simulation data as per relevant ISO standards.

Ride is essentially the outcome of coupled dynamics of various involved sub-systems which make it too complex to deal analytically. Tires, amongst these, are known to be highly nonlinear compliant systems. Selection of tires specifications such as rated tyre pressure, etc. are generally decided through subjective assessment. While experts agree that tyre pressure affects the attributes such as ride to a noticeable degree, the quantification of the change often remains missing. In the current work, vibration levels of various sub-systems relevant to ride in an SUV are measured for three different tyre pressures at different speeds over the three randomly generated roads. For the purpose, artificial road profiles of classes A, B and C are synthesized from the spectrum of road classes defined in ISO 8608:2016 and reproduced on a four-poster test rig.

Active suspension systems employ sophisticated control algorithms to deliver superior comfort in vehicles. However, the capabilities of these algorithms are limited by the physical constraints of actuators. Many vehicles use hydraulic actuators in their active suspension system, which use fluid movement to control suspension motion. These systems inherently have slower response times due to the nature of fluid flow and the time required to build up or release pressure within the hydraulic system. Typically, hydraulic systems operate in a low bandwidth of 0-5 Hz. This limits their capability to only meeting vehicle’s primary ride targets which typically lie below 5 Hz. Although they can be tuned to operate at a slightly higher frequency range (up to 10 Hz), they perform poorly in attenuating the secondary ride vibration, i.e., 5 – 25 Hz.