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The Indian automotive industry is going through a rapid transformation phase. Regulatory emission norms such as, migration from BSIV to BSVI engine, increased adoption of μ-hybrid, full electric and autonomous cars are examples of such rapid transformation. The upgradation of internal combustion engines for compliance with new regulatory norms (e.g., from BSIV to BSVI) has caused a significant change in the automotive acoustic performance. As the powertrain system are being upgraded and getting quieter, the on-board Heating, Ventilation and Air-Conditioning system (HVAC) system emerges as one of the prominent noise sources which strongly influences overall refinement levels inside the cabin. This in turns is affecting overall feeling of passenger’s comfort. The HVAC system of an automobile is a compact and yet a complex system designed to provide thermal comfort inside the car cabin.

Design of HVAC system plays an important role in acoustic comfort for passengers. With automotive world moving towards electrical vehicles where powertrain noise is low, designing low noise HVAC system is becoming more important. For an automobile manufacturer, ability to predict the production vehicle cabin noise at the early design stage is important as it allows more freedom for design changes, which can be incorporated in the vehicle at lower cost. Although HVAC prototype and system level testing at early design stage is possible for noise estimation but flow field is not visible in test that makes difficult to improve design. CFD simulation can provide detailed information on flow field, noise source strength and location. But in such a simulation, accurate prediction has been a challenge due to the inability of CFD tools to model acoustic absorptive characteristics of interior walls of cabin.

Vehicle refinement from point of view reduction in its Noise, Vibrations and Harshness (NVH) affects customer’s buying decision and it also directly influences his/her driving experience on road at different speeds. Customer voice, however, indicates that a traditional process of developing design solutions is not aligned with the customers’ expectations. Traditionally the load cases for NVH development are focused only on quietness of passengers’ cabin at idling and in 3rd gear wide open throttle cruising on smooth roads. In reality, the Driver of a premium sedan car or a Sports Utility Vehicle (SUV) or a Compact Utility Vehicle (CUV) expects something different than merely the low sound pressure level inside the cabin. His/her driving pattern over a day plays a crucial role. A vehicle-owner wishes to balance various attributes of the in-cab sound and tactile vibrations at a time.

Passenger utility vehicles like car, SUVs, MPVs are used in wide application all over the world. Luxuries are becoming essential features of product mix along with comfort and ergonomics. Customer desires best shift quality with emerging technologies like AT, DCT, CVT, etc. and every OEM is working hard to achieve it. It is very difficult to satisfy the customer desire because of diversities in demographics and geographic. Gear shift quality (GSQ) is very crucial touch point in overall drive feel of vehicle. It consist of various parameters like mode selection feel, precision, comfort, select Noise, etc. It demands tradeoff practices among various parameters as stated. In this paper, external mode selection system of automatic transmission is explained. Various contributing parameters are explained with practical design approach for detent profile, mode selection mechanism, cable & dampers, etc.

Cabin noise is a significant product quality criteria which enables the customers for product differentiation. There are various sources of cabin noise such as wind, structures(panels), engine, suspension, tire and roads. During product development phase, extensive tests has been conducted to improve vehicle dynamics behavior on various climatic conditions. One such test is accelerating vehicle on low mu or icy surface. While performing acceleration manoeuvre (tractions) on a low mu tracks, Cabin noise with source identified from front underbody & low tractive torque build up is reported. This undesirable behavior may occur due to following reason (1) Excitation of coupled modes between suspension and powertrain which induces torque fluctuation. (2) Transmissibility of various subsystem can be the reason for above problem statement. (3) Poorly chosen tire compounds and design leads to fluctuation in torque.

Nowadays, a higher amount of time is being spent inside the vehicles on account of varied reasons like traffic, longer distances being travelled and leisure rides. As a result, better comfort and convenience features are added to make the driver and passenger feel at ease. Thermal comfort and acoustic isolation are the primary parameters looked at by both the customers and the original equipment manufacturers. Seats are one of the primary touch points inside the vehicle. Perspiration caused at the contact patch areas between the seats and passengers leads to high thermal discomfort. A ventilated seat, with or without an air-conditioning system, is one such attribute offered to improve passenger thermal comfort. Ventilation becomes even more essential for front-row seats, as these are more likely to be exposed to external solar loading through the front windshield.

HVAC system design has an accountability towards acoustic comfort of passengers of a vehicle. Owing to larger cabin volume of a bus, multiple air blowers have to be installed to ensure comfort of passengers. Such multiple blowers produce significant flow induced noise inside the cabin. For commercial success, it becomes essential to predict intensity of such a flow induced noise at very early stages in product development. Conventionally sliding mesh based CFD approach is deployed to predict flow and turbulence noise around each blower. However due to complexity, this method becomes computationally intensive resulting in cost and time inefficiency. Hence it is desirable to innovate around an alternative rapid, reliable prediction method, which ensures quick turnaround of prediction.