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Drive cycles have been an integral part of emission tests and virtual simulations for decades. A drive cycle is a representation of running behavior of a typical vehicle, involving the drive pattern, road characteristics and traffic characteristics. Drive cycles are typically used to assess vehicle performance parameters, perform system sizing and perform accelerated testing on a test bed or a virtual test environment, hence reducing the expenses on road tests. This study is an attempt to design a relatively robust process to generate a real world drive cycle. It is based on a Six Sigma design approach which utilizes data acquired from real world road trials. It explicitly describes the process of generating a drive cycle which closely represents the real world road drive scenario. The study also focuses on validation of the process by simulation and statistical analysis.

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.

Vehicle lateral dynamic response parameters such as yaw velocity, lateral acceleration, roll angle, etc. depend on the nature of steering input. Response parameters vary with the amplitude and frequency of steering input. This paper deals with developing insights into the effect of steering input frequency on transient handling dynamics. For the purpose two SUV segment vehicles with similar curb weight are considered. Vehicles are given pulse inputs of the amplitudes corresponding to 4 m/s2 steady state lateral acceleration and target speeds of 80 kmph and 100 kmph, as recommended in ISO 7401:2011. Steering inputs are executed using a Steering Robot (ABD SR30). Lateral transient dynamic response gains as well as natural frequencies of yaw are studied for 0-2 Hz input frequencies. Several insights are developed, adding to the understanding of transient lateral dynamics and its relationship with steering input.

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.

In recent times, Battery electric vehicles (BEV) have gained a lot of popularity since they can contribute immensely to control the urban air pollution. However, to consider the BEVs as a sustainable mobility solution, a significant improvement is needed in several aspects including performance, range, cost, weight and recharging time. In the present work, the acceleration performance of an electric vehicle is improved to match with its diesel variant by optimizing the accelerator pedal map strategy. Due to weight and cost constraints, the battery and electric machine capacity of the electric variant of the vehicle was considerably lower (41 % lesser power and 44% lesser torque). However, the expectation from the customers is to have no noticeable difference in the low-end performance feel between the variants.

Globally, automotive sector is moving towards improving off-road performance, durability and safety. Need of off-road performance leads to unpredictable overload to powertrain system due to unpaved roads and abuse driving conditions. Generally, shafts and gears in the transmission system are designed to meet infinite life. But, under abuse condition, it undergo overloads in both torsional and bending modes and finally, weak part in the entire system tend to fail first. This paper represents the failure analysis of one such an incident happened in output shaft under abuse test condition. Failure mode was confirmed as torsional overload using Stereo microscope and SEM. Application stress and shear strength of the shaft was calculated and found overstressing was the cause of failure. To avoid recurrence of breakage, improvement options were identified and subjected to static torsional test to quantify the improvement level.

Ride is an important attribute which must be accounted in the passenger segment vehicles. Excessive H point acceleration, Steering wheel acceleration, Pitch acceleration can reduce the comfort of the driver and the passengers during high frequency and low frequency rough road events. Excessive Understeer gradient, roll gradient, roll acceleration and Sprung mass lift could affect the Vehicle driver interaction during Steady state cornering, Braking and Step steer events. The concept architecture of the vehicle plays an important role in how comfort the vehicle will be. This paper discusses how to improve SUV ride performances by keeping handling performance attributes same or better than base vehicle. Multi Objective Optimization was carried out by keeping spring, bushing and damper characteristic as the design variables to avoid new system or component development time and cost.