Electrification of automobiles results in new and challenging characteristics of vehicle NVH (Noise, Vibration, and Harshness) and ride comfort. Optimized architecture of electric vehicles has been evolved for appropriate placement of electric power drives. This paper presents the experiments performed for order analysis technique to predict the vibrational behavior of conventional and electric scooters which was not used in 2-wheelers earlier and used for 4-wheeler noise predictions and for vibration analysis of rotating machinery. Vibrational analysis of source alone in conventional and electric two-wheelers carried out by order analysis and the result is presented through Campbell Diagrams to observe the critical orders along with the variation of the amplitude of vibration as a function of frequency. Target locations’ Vibration Dose Values (VDV) is calculated to assess rider comfort and is compared with the ISO 2631 standard. The higher amplitude of vibration has been observed at 23rd order for electric scooter while for conventional scooter it is noted at 8th and 16th order with reference to the wheel speed. Compared to the conventional scooter, electric scooter exhibits very low overall vibration level and range is away from human perception range resulting in good comfort.
The pneumatic tire is one of the important sources of noise and vibration in a vehicle. Modern vehicles have implemented good preventive and control measures for power unit and aerodynamic NVH. Hence, the tire/road interaction has become a dominant source. Riegel and Wiedemann [1] have reported the dominance of tire/road interaction over engine and wind sources, in contributing to vehicle interior noise. Vehicle interior noise due to tire/road interaction consists of two components, namely structure borne noise caused due to low frequency excitation (below 500 Hz) and air borne component which are due to mid and high frequency excitation (above 500 Hz). Experimental Transfer Path Analysis (TPA) is a tool to identify whether the source or transmission path needs to be altered for reducing the cabin noise. This paper describes the successful implementation of experimental TPA to synthesize structure borne vehicle interior noise due to tire/road interaction on a sedan class passenger car.
As a first step, the required local structural Frequency Response Functions (FRFs) and Noise Transfer Functions (NTFs) are determined in the laboratory for the vehicle without tire/wheel assembly by hammer impact test, by hitting at the spindle interface (paths). The second step is to repeat the test with tire/wheel assembly by an impact on the tire at the contact patch to get the same set of structural FRFs. The third step is to conduct a road test. The operational acceleration responses as well as interior sound pressure levels are measured for both engine on and off conditions for the same measurement points considered during the laboratory tests. These operational data are further combined with local structural FRFs of the vehicle to estimate the operational loads at the transfer paths using matrix inversion method. Then, the NTFs are multiplied with operational loads to synthesis the contribution of individual paths to the total structure borne vehicle interior noise. Lastly, path and vector contribution analysis are carried out from the TPA results to identify the critical paths for the critical frequencies. Moreover in this work the TPA is not only used to synthesize the structure borne interior noise, but also to estimate the road input excitation. Hence the tire force transmissibility from contact patch to vehicle spindle is determined. The estimated road excitation can be used in a parametric study to address the influence of tire design in contributing to structure borne vehicle interior noise.
Lateral dynamics of a road vehicle refers to its directional control and stability. Bicycle model is the classical proven model for this study. This paper presents a4 degrees of freedom mathematical model, representing a three-axle tractor semitrailer, to investigate its yaw stability in combined cornering and braking manoeuvres. The equations of motion governing the system are derived using Newtonian mechanics and then converted into a state space form for simulation. A non-linear tire model and a load transfer model are implemented to accurately incorporate the effect of braking on yaw stability. In the first step, steady state analysis is performed to determine the variation of steady state gain characteristics such as yaw velocity gain and articulation angle gain for different loading conditions of the vehicle. Yaw response characteristics such as articulation angle, articulation rate, lateral velocity and yaw rate are simulated in MATLAB. In the second step, the directional responses of the vehicle during jackknifing and trailer swing are studied by performing simulations under wheel lock-up condition on different axles and are compared with the no-wheel-lock up condition. Eigen value analysis is used to observe the variation in stability under different simulation conditions. Finally in the third step the effect of increasing forward speed on the stability is also simulated.
Handling characteristics of any vehicle refer to its directional control and stability for given steering input. The vehicle parameters such as mass, mass moment of inertia and location of C.G. play a vital role and decide handling response of vehicle under different scenarios. Safe drive is ensured by vehicle’s responses such as yaw rate, roll rate and vehicle lateral acceleration. This paper presents steady state and transient state simulation of XUV 500 model in accordance with ISO 4138 and ISO 3888 test standards using CarSim-Simulink Co-simulation. Influence of changes in above mentioned parameters on Vehicle response during both tests is investigated. Further, control of power train output using torque vectoring is implemented in both tests and its effect on vehicle response is evaluated. The results show that understeer tendency of the vehicle is reduced in steady state test (Constant radius test: ISO 4138). Critical vehicle responses of yaw rate, roll rate, lateral acceleration and path tracking showed improvement during the DLC manoeuvre (ISO 3888) hence, improving stability at higher lateral accelerations.
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