Tata Technologies Limited is a company in the Tata Group that provides services in engineering and design, product lifecycle management, manufacturing, product development, and IT service management to automotive and aerospace original equipment manufacturers and their suppliers. It is a subsidiary of Tata Motors. The company is active in North America, Europe, the Middle East and the Asia Pacific region..
The evolution of electric vehicles (EVs) also demands the evolution of powertrain mounting systems to achieve superior Noise, Vibration, and Harshness (NVH) performance. This study presents a comparative evaluation of cradle, saddle and ladder mounting systems in EV applications. Examples of experimental modal analysis and vehicle-level vibration tests were performed in order to evaluate structure-borne noise transmission as well as airborne noise transfer under operating conditions. Important parameters like mount stiffness, isolation efficiency and dynamic load distribution were performed. These findings provide valuable guidance for selecting optimal mount strategies to enhance occupant comfort and acoustic quality in future EV designs. Recommendations for mount system improvements considering evolving EV architectures are also discussed. This work provides a crucial, experimentally-validated framework for selecting optimal mounting architectures, addressing a key gap in the transition from ICE-based intuition to EV-specific design principles.
Affordable and clean energy has been one of the major objectives adopted by United Nations under the 2030 Agenda for Sustainable Development. In this direction, fuel cell electric vehicles have gained popularity in recent times due their efficiency and environmental friendliness. Fundamentally, it uses compressed hydrogen from the vehicle-mounted tank and combines with ambient air to generate DC electricity. Water is created as a by-product and expelled through the tailpipe. The technology being integrated on powertrain architecture, along with battery pack can prove to be an efficacious approach for zero emission automotive system. However, hydrogen being the primary fuel, and being stored at high pressure, the system involves handling and potential hazards of hydrogen, and possibility of explosions due to hydrogen leaks. Hence, safety is the key issue in handling fuel cell vehicles. This paper discusses about role of Unified Diagnostic Services (UDS) in providing safety and precautionary aspects for the fuel cell vehicles. UDS has been first time developed for fuel cell vehicle, in India in accordance with fault codes by fuel cell stack, applied on TML FCEV bus. It discuss about how UDS can be used to anticipate key safety issues such as hydrogen leaks, pressure monitoring system, and analyzing the Diagnostic Troubleshooting Codes (DTC) from fuel cell stack. In order to improve the dependability, durability, and safety of fuel cell vehicles (FCVs), diagnostic services are essential since they assist in the real-time detection and identification of defects. Apart from identifying DTC codes from the stack, this paper also discuss about how the key UDS services like, diagnostic and communication management services, data transmission services, input output control services, etc. can be implemented for the fuel cell controller unit (FECU). As a part of novelty, the role of AUTOSAR modules such as DEM and DCM in handling the faults has also been discussed in brief.
The automotive industry’s future is increasingly centered around electric vehicles (EVs), driven by the imperative to combat global warming and fulfill customer expectations. This paper investigates the EV technology landscape within the Indian automotive sector, identifying the unique challenges present in the Indian market. Furthermore, it provides an in-depth analysis of EV components, architecture, and the packaging of aggregates. To substantiate our study, we have conducted a comprehensive case study on Tata Motors, examining their EV manufacturing strategies and the obstacles they face.
In automotive suspension systems, components like bump stoppers and jounce bumpers play critical roles in controlling suspension travel and enhancing ride comfort. Material selection for these components is driven by functional demands and performance criteria. Traditionally, Natural rubber (NR) has traditionally been favored for bump stopper applications due to its excellent vibration absorption, tear resistance, cost-effectiveness, and biodegradability. However, in more demanding environments, it has been largely replaced by microcellular polyurethane (PU) elastomers, which offer superior durability, environmental resistance, and enhanced noise, vibration, and harshness (NVH) performance. This study revisits NR with the goal of re-establishing its viability by enhancing its performance to match or surpass that of PU. Through compound optimization and advanced material processing techniques, significant improvements have been achieved in NR’s mechanical strength, compression set resistance, and environmental durability. Also a convolute bump stopper design was explored to enhance energy absorption and packaging efficiency. Compared to traditional solid profiles, the convoluted geometry provided progressive stiffness characteristics, improved deformation control, and optimized ride comfort under dynamic loading conditions. Traditional NR design and formulation were compared against PU and next-generation NR in terms of Aging Durability Factor, stiffness, fatigue durability, vehicle-level buzz, squeak, and rattle (BSR), as well as ride and handling performance. A comparative assessment of carbon emissions between PU and NR was also conducted to evaluate environmental impact. The result is a next-generation NR formulation that delivers performance comparable to PU while retaining the ecological and economic advantages of natural rubber. This research demonstrates a sustainable pathway toward high-performance elastomeric materials, bridging the gap between conventional and advanced solutions in modern engineering applications.
In the current scenario of EV revolution in the automotive industry, NVH performance of the vehicles is one of the major points of sale to the customers. Auxiliary components play one of the predominant roles in the contribution of noise to overall vehicle interior or exterior sound pressure levels, which impact customer vehicle comfort. CAE prediction of NVH performance of automotive components involves a lot of design iterative processes, large server space utilization, and time-consuming. To reduce cost and time, data-driven technologies like AI algorithms can help CAE engineers because of their high efficiency and high precision. In the current research, a wiper motor mount stiffness prediction algorithm was designed based on the historical data using CAE analysis and AI algorithms, and improved prediction accuracy by tuning the parameters of AI algorithms using grid search methodology. High prediction accuracy of wiper motor mount stiffness has been achieved with the method of support vector machine. CAE engineers can avoid iterative processes by utilizing the optimized design parameters from the prediction results without running full finite element analysis simulations.
