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Advanced Non-linear topology optimization methods have been addressed as the most promising techniques for light weight and performance design of Powertrain structures. The theoretical achievements are obtained both mechanically and mathematically. Nowadays, the great challenge lies in solving more complicated engineering design problems with multidisciplinary objectives or complex structural systems. The purpose of this paper is to provide a forum to present new developments in structural Non-linear topology optimization. The advantage of the proposed method is that structural optimization on irregular design domains can be carried out easily. Furthermore, this method integrates the stress analysis and the boundary evolution within the framework of finite element methods. In this paper, mainly focused on the Commercial Vehicles Powertrain component i.e. Transmission Housing.

Brake drum in commercial vehicles is very important aggregate contributing towards major weight in brake system module. The main function of brake drum is to dissipate kinetic energy of vehicle into thermal energy, as a results in braking operation major load comes on brake drum. Hence this is very critical component for vehicle safety and stability [1]. Objective of this paper is to increase the pay load, which is utmost important parameter for commercial vehicle end customers. To achieve the light weighing target, alternate materials such as Spheroidal graphite iron (SGI) has been evaluated for development of brake drum. Many critical parameters in terms of reliability, safety and durability, thickness of hub, wheel loading, heat generation on drum, manufacturing and assembly process are taken into consideration. The sensitivity of these parameters is studied for optimum design, could be chosen complying each other’s values.

The Advancement in Connected vehicles Technology in recent years has propelled the use of concepts like the Internet of Things (IoT) and big data in the automotive industry. The progressive electrification of the powertrain has led to the integration of various sensors in the vehicle. The data generated by these sensors are continuously streamed through a telematics device on the vehicle. Data analytics of this data can lead to a variety of applications. Predictive maintenance is one such area where machine learning algorithms are applied to relevant data to predict failure. Field vehicle malfunction or breakdown is costly for manufacturers’ aftermarket services. In the case of commercial vehicles, downtime is the biggest concern for the customer. The use of predictive maintenance techniques can prevent many critical failures by tending to the root cause in the early stages of failure. Engine overheating is one such problem that transpires in diesel engines.

Drink & drive has caused the increased rate of commercial vehicle accidents in the world due to the slow response to judgment and reasoning. According to research study 70% accidents are happened due to drunk & drive, it causes loss of human life and economic damage. Research has proven that drunk drivers exhibit aggressive driving behavior and apply more force during braking. While public health awareness and legal restrictions can assist in educating and discouraging people from drunk & drive, a more fool-proof method is not available in the market for commercial vehicles. Currently, a low cost, fail-safe onboard alcohol detection, and vehicle safety system is the need of the hour. This paper deals with the design & development of a low cost active onboard breath alcohol detection system and it’s on vehicle validation. Further, it explains the type of alcohol detection sensor used, controller design, logic programming and system packaging.

The reduction of tire wear in vehicle is one of the major challenges for engineers. Under-inflated tire can cause reduction in tire life along with decrease in driving stability of vehicle. Efforts have been taken to develop a low-cost auto-tire inflation system integrated in vehicle for reduction in tire wear as well as to avoid periodic checks of tire pressure. This paper deals with the technology and design approach required in the development of auto-tire inflation system for commercial vehicle. This system should have the fundamental role of not only monitoring the tire pressure but also inflating the tire to the recommended level of pressure whenever the pressure is reduced below the recommended level. Different approaches have been worked out for integration of system on vehicle with least modification in existing design.

To compete with the current market trends there is always a need to arrive at a cost effective and light weight designs. For Commercial Vehicles, an attempt is made to replace existing Gear Shift Fork from FC Iron (Ferro Cast Iron) to ADC (Aluminum Die Casting) without compromising its strength & stiffness, considering/bearing all the worst road load cases and severe environmental conditions. ADC has good mechanical and thermal properties compared to FC Iron. Feasible design has been Optimized within the given design space with an extra supporting pad for load distribution. Optimization, Stiffness, Contact pattern has been done using OptiStruct, Nastran & Ansys for CAE evaluation. A 6-speed manual transmission is used as an example to illustrate the simulation and validation of the optimized design. Advanced linear topology optimization methods have been addressed as the most promising techniques for light weighting and performance design of Powertrain structures.