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In recent years, the push for reduced product development timelines has been more than ever with significant changes in the automotive market. High electrification, intelligent vehicle systems and increased number for car manufacturers are a few key drivers to the same. The front loading of development activities is now a key focus area for achieving faster product development. From vehicle dynamics point of view availability of subjective evaluation feedback plays a key role in optimization various system specifications. This paper discusses an approach for front loading through parallel development of the tire and vehicle chassis system, using advanced simulation and driving simulator technology. The proposed methodology uses virtual tire models which in combination with real-time vehicle model enables subjective evaluation of vehicle performance in driver-in-loop simulators.

Modern day automotive market demands shorter time to market. Traditional product development involves design, virtual simulation, testing and launch. Considerable amount of time being spent on virtual validation phase of product development cycle can be saved by implementing machine learning based predictive models for key performance predictions instead of traditional CAE. Durability oil canning loadcase for vehicle hood which impacts outer styling and involves time consuming CAE workflow takes around 11 days to complete analysis at all locations. Historical oil canning CAE results can be used to build ML model and predict key oil canning performances. This enables faster decision making and first-time right design. In this paper, prediction of buckling behaviour and maximum displacement of vehicle hood using ML based predictive model are presented. Key results from past CAE analysis are used for training and validating the predictive model.

Computer Aided Engineering (CAE) simulations are an integral part of the product development process in an automotive industry. The conventional approach involving pre-processing, solving and post-processing is highly time-consuming. Emerging digital technologies such as Machine Learning (ML) can be implemented in early stage of product development cycle to predict key performances without need of traditional CAE. Oil Canning loadcase simulates the displacement and buckling behavior of vehicle outer styling panels. A ML model trained using historical oil canning simulation results can be used to predict the maximum displacement and classify buckling locations. This enables product development team in faster decision making and reduces overall turnaround time. Oil canning FE model features such as stiffness, distance from constraints, etc., are extracted for training database of the ML model. Initially, 32 model features were extracted from the FE model.

Child injury performance evaluation is becoming critical part of almost all legal and consumer ratings-based vehicle safety evaluation protocols. Most of New CAR Assessment Programs (NCAP) now have separate ratings exclusively to evaluate child restraint system effectiveness and child dummy performance under various crash testing modes. OEM’s have need and challenge to maximize injury performance. Sled tests are conventionally used for tuning restraints like seat belts and airbags for driver and co-driver under various frontal type test conditions. However, second row seats are used for CRS/ Child injury performance evaluations. In the present study an attempt is made to simulate child injury performance of P3 dummy positioned on second row seat on defined child seat for 64 kmph frontal Offset deformable barrier type test conforming to Global NCAP. Sled pulses are carefully tuned to capture key injury patterns. Thence restraint parameters are tuned to improve child dummy injuries

Dual mass flywheel (DMF) is an excellent solution to improve the noise, vibration and harshness (NVH) characteristic of any vehicle by isolating the driveline from the engine torsional vibrations. For the same reason, DMFs are widely used in high power-density diesel and gasoline engines. However, the real-world usage conditions pose a lot of challenges to the structural robustness of the DMF. In the present work, a new methodology is developed to evaluate the robustness of a DMF fitted in a compact sports utility vehicle (SUV) with rear-wheel drive architecture. The abuse conditions (mis-gear, sudden braking, etc) in the real-world usage could lead to a sudden engine stall leading to an abnormally high angular deceleration of the driveline components. The higher rate of deceleration coupled with the higher rotational moment of inertia of the systems might end up in introducing a significantly high impact torque on the DMF.

Vehicle safety and adherence to rules and regulation is of utmost requirement for any OEM. ECE R42 is one of the most important test criteria for a vehicle to get launched. To prove this, we shall discuss the case of Low speed impact structure construction. In this paper, we are going to demonstrate the novel design of Polymer energy absorption structure to meet the rear bumper low speed impact test and ensure proper absorption of impact energy and avoid any damage to rear lamp of the vehicle. This paper shows a perfect example of sustainability with the help of complete modular construction of the frame structure. The proposed design uses a cost-effective way of assembling the physical part by comparing with benchmarking and within the Mahindra part library. The low speed impact structure is mounted directly to BIW panels without any extra foams. These frame structure are simple in design and rigid in construction by comparing with other OEM products and within all Mahindra vehicles.

During design and development of a cabin for any commercial vehicle, meeting the strength requirements of front impact as per Indian regulation (AIS-029) is a very critical milestone. AIS-029 regulation consists of three destructive tests, i.e. Front Impact Test (Test A), Roof Strength (Test B) and Rear Wall Strength (Test C). Study of energy absorbing front cabin mount, its stiffness balance with chassis and CAE correlation with physical test is demonstrated in this study. [1]

New trend in steering system such as EPS is coming up, but still hydraulic power steering system is more prevalent in today’s vehicles. Power steering pump is a vital component of hydraulic power steering system. Failure of steering pump can lead to loss of power assistance. Prediction of hub load on pump shaft is an important design input for pump manufacturer. Higher hub loads than the actual designed load of pump bearing may lead to seizure of pump. Pump manufacturer has safe limits for hub load. Simulations can assist for optimization of belt layout and placement of accessories to reduce the hub load. Lower hub load can have direct effect on improvement of pump durability. This paper deals with dynamic simulation of belt drive system in MSC.ADAMS as well as vehicle level measurement of hub load on power steering pump.

Twist beam is a type of suspension system that is based on an H or C shaped member typically used as a rear suspension system in small and medium sized cars. The front of the H member is connected to the body through rubber bushings and the rear portion carries the stub axle assembly. Suspension systems are usually subjected to multi-axial loads in service viz. vertical, longitudinal and lateral in the descending order of magnitude. Lab tests primarily include the roll durability of the twist beam wherein both the trailing arms are in out of phase and a lateral load test. Other tests involve testing the twist beam at the vehicle level either in multi-channel road simulators or driving the vehicle on the test tracks. This is highly time consuming and requires a full vehicle and longer product development time. Limited information is available in the fatigue life comparison of multi-axial loading vs pure roll or lateral load tests.

Today’s automotive world has moved towards an age where safety of a vehicle is given the topmost priority. Many stringent crash norms and testing methodology has been defined in order to evaluate the safety of a vehicle prior to its launch in a particular market. If the vehicle fails to meet any of these criteria then it is debarred from that particular market. With such stringent norms and regulations in place it becomes quite important on the engineer’s part to define the structural requirements and protect the space to meet the same. If the concept level platform definition is done properly it becomes very easy to achieve the crash targets with less cost and weight impact.