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First time right vehicle performance and time to market, remains all automotive OEMs top priority, to remain competitive. NVH performance of product communicates impression to customer, remains one of the most important and complex attribute to meet, considering performances to be met for 20 Hz -6000 Hz. Frontloading techniques (FEM/BEM/SEA/MBD) for NVH are critical and necessary to achieve first time right NVH performance. Objective of this paper is to present a frontloading approach for automotive sound package optimization (absorber, barrier and damper elements) for SUV vehicle. Current process of designing sound package is mainly based on experience, competitive benchmarking of predecessor products. This process (current process) heavily depend on testing and validation at physical prototype and happens at later stages of program, especially on tooled up body.

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.

There is a growing need for the accurate Computer Aided Engineering (CAE) models for vehicle performance evaluation. The reduced product development time and complexity of the vehicle evaluation demands accurate prediction with CAE models. Vehicle dynamics performance evaluation is very critical in vehicle development process, which require very accurate vehicle and tire models. The tire characteristics are represented as mathematical, physics based and empirical models. There are different types of tire models exist like Fiala, PAC, SWIFT and FTire etc, which can be used for vehicle handling, ride and steering performance evaluation. There is a need to study and understand these tire models before applying to specific vehicle dynamic performance. There is a challenge to get the tire models as tire modeling require lot of tests and time consuming.

Increasing complexity in E/E architecture poses several challenges in developing comfortable, clean and safe cars. This mandates robust processes to mitigate potential hazards due to malfunction of electronic systems throughout the product life cycle. With the advent of ISO 26262 [1] which provides guidelines for developing safe cars, the process is getting standardized towards safer mobility. In this paper, the functional safety process is briefly covered and a case study of Hazard Analysis and Risk Assessment for specific E/E system is presented. An in-house tool developed for functional safety process and management is covered.

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.

Hydraulic Load sensing brake valves are used in vehicles from a long time in the market. They proportionate the rear brake line pressure according to the rear axle load in order to avoid the rear wheel lock during braking. During the actual test of the Hydraulic load sensing valve on a subject vehicle, there was drop in performance against its expected peak brake performance. In the current work a detailed analysis is made to understand the sensitivity of the load sensing valve & its effect on the vehicle performance. The parameters affecting the valve sensitivity along with vehicle level factors affecting the performance are analysed during the work.

Meeting various customer(s) requirements with the given automotive product portfolio within the stipulated time period is a challenge. Design of product configuration matrix is an intelligent task and it requires information about vehicle performance for different configurations which helps in deciding the level of new development. Most often the situation arises, particularly in the field of NVH, to strike the right balance between engine power and structural parameters of the body. The sensitivity of engine power on the overall NVH behavior is the key information necessary to take major business decisions. In this paper, the effect of change in torsional fluctuation of the engine on the NVH behavior of the rear wheel drive vehicle is experimentally studied. The torsional fluctuation of the driveline is given as an input with the help of an electric motor to the existing test vehicle at its differential end and the current NVH levels are measured.

Customer perceived quality (CPQ) of the car is the impression of excellence that a customer experiences the brand through sight, sound, touch, and scent. Molded-in-color (MIC) bumper’s aesthetic appeal contributes significantly to the CPQ of the car. Typical parameters used to define CPQ are color, gloss, grain definition, grain depth, geometry and draft. In this work the durability of the color and gloss post ageing is understood by using analytical and characterization tools. Using the results of ageing characterization, an attempt has been made to understand the retained newness of MIC bumper.

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.

A major challenge for combustion engine development is to optimize the engine for improved fuel economy, reduce greenhouse gases. Stringent CAFÉ and emission norms require the customer to pay higher capital on vehicles. To offset the cost of ownership- cheaper and alternative energy sources are being explored. Ethanol blend with regular Gasoline, and CNG are such alternative fuels. Reducing the consumption of Gasoline also helps India’s dependence on import of crude oil. The study was carried on turbo-charged gasoline direct injection engine. The effect of ethanol on engine and vehicle performance is estimated and simulated numerically. The work is split into three stages: first the base 1D engine performance model was calibrated to match the experimental data. In parallel, vehicle level Simulink model was built and calibrated to match the NEDC cycle performance.

The input shafts are conventionally developed through Hot forging route. Considering upcoming new technologies the same part was developed through cold forging route which resulting in better Mechanical properties than existing hot forging process. It has added benefit of cost as well as environmental friendly. Generally, the part like Input shaft which having gear teeth, splines etc., will be manufactured through Hot forging process due to degree of deformation, availability of press capacity, diameter variations etc., This process consumes more energy in terms of electricity for heating the bar and also creates pollution to the atmosphere. Automotive input shaft design modified to accommodate cold forging process route to develop the shaft with press capacity of 2500T which gives considerable benefit in terms of mechanical and metallurgical Properties, close dimensional tolerances, less machining time, higher material yield when compared to hot forging and metal cutting operation.

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.

Light weighting is an effective strategy in increasing energy efficiency in the automotive industry. In this paper, mass reduction with cost benefit was targeted in an exterior trim panel. Polypropylene copolymer (PPCP) compound was developed for a large exterior trim panel (1400 X 700mm) having an integrated grill mesh. The part had challenging requirements in terms of slow speed impact, structural durability, dimensional stability, aesthetics, thermal ageing resistance, cold impact resistance, scratch resistance and weathering resistance. By having ultra-high flow behavior, optimum tensile strength, modulus, impact strength and thermal properties, the PPCP compound met the requirements for a thin wall exterior trim panel with a thickness of 2.6mm. Structural durability of the design was validated by virtual engineering. Part design and material combinations with better tooling design iterations were analyzed by using mold flow analysis.

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.