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Lubrication systems play a major role not only in the durability of modern IC engines but also in performance and emissions. The design of the lubrication system influences the brake thermal efficiency of the engine. Also, efficient lubrication reduces the engine's CO2 emissions significantly. Thus, it is critical for an IC engine to have a well-designed lubrication system that performs efficiently at all engine operating conditions. The conventional lubrication system has a fixed-displacement oil pump that can cater to a particular speed range. However, a fully variable displacement oil pump can cater to a wide range of speeds, thereby enhancing the engine fuel efficiency as the oil flow rates can be controlled precisely based on the engine speed and load conditions. This paper primarily discusses the optimization of a lubrication system with a Variable Displacement Oil Pump (VDOP) and a map-controlled Piston Cooling Jet (PCJ) for a passenger car diesel engine.

Leaf Springs are commonly used as a suspension in heavy commercial vehicles for higher load carrying capacity. The leaf springs connect the vehicle body with road profile through the axle & tire assembly. It provides the relative motion between the vehicle body and road profile to improve the ride & handling performance. The leaf springs are designed to provide linear stiffness and uniform strength characteristics throughout its travel. Leaf springs are generally subjected to dynamic loads which are induced due to different road profiles & driving patterns. Leaf spring design should be robust as any failure in leaf springs will put vehicle safety at risk and cost the vehicle manufacturer their reputation. The design of a leaf spring based on conventional methods predicts the higher stress levels at the leaf spring center clamp location and stress levels gradually reduce from the center to free ends of the leaf spring.

The focus on driver and occupant safety as well as comfort is increasing rapidly while designing commercial vehicles in India. Improvements in the road network have enhanced road transport for commercial vehicles. Apart from the cost of operation and fuel economy, the commercial vehicles must deliver goods within stipulated time. These factors resulted in higher speed of operation for commercial vehicles. The design should not compromise the safety of the vehicle at these higher speeds of operation. The vehicle should obey the driver’s intended direction at all speeds and the response of the vehicle to driver input must be predictable without much larger surprises which can lead to accidents. The commercial vehicles are designed with rigid axle and RCB type steering system. This suspension and steering design combination introduce steering errors when vehicle travel over bump, braked and while cornering.

In farm tractors, the available drawbar power, and Power Take-Off (PTO) power are generally lower than the engine power due to parasitic losses. These losses are caused by engine-driven auxiliary loads such as cooling fans, hydraulic pumps for power steering, alternators, etc. Minimizing these parasitic losses can increase the available drawbar power and PTO power, resulting in direct fuel savings by reducing fuel consumption. The continuous increase in fuel costs and the environmental impact of emitted gases from burned fuel into the atmosphere have necessitated the replacement of hydraulic power steering and mechanical fans with Electric Power Steering (EPS) and electric fans, respectively, to improve efficiency. The existing battery has been replaced with a higher capacity battery to provide power to the electric fan, electric power steering, and other electrical components.

The automobile industry is going through one of the most challenging times, with increased competition in the market which is enforcing competitive prices of the products along with meeting the stringent emission norms. One such requirement for BS6 phase 2 emission norms is monitoring for partial failure of the component if the tailpipe emissions are higher than the OBD limits. Recently PM (soot) sensor is employed for partial failure monitoring of DPF in diesel passenger cars.. PM sensor detects soot leakage in case of DPF substrate failure. There is a cost factor along with extensive calibration efforts which are needed to ensure sensor works flawlessly. This paper deals with the development of an algorithm with which robust detection of DPF substrate failure is achieved without addition of any sensor in the aftertreatment system.

Powertrain complexity rapidly increasing to meet fast moving regulation requirements. The BS6 Phase-1 regulation norms were implemented in India from April 1, 2020 and replaced the previous BS4 norms. Phase-2 of the BS6 regulation norms were came into effect on April 1, 2023. To meet this stringent regulation requirement, need effective performance of after treatment systems like DOC, DPF and SCR demands critical hardware selection and implementation. In Indian market, LCV application is cost sensitive and highly competitive where operational cost is most critical factor. Naturally aspirated engine has less operating cost, which is the best for LCV applications, but is has its own challenges to meet BS6 norms like higher engine out NOx, dynamic temperature profiles etc. A robust DeNOx emissions strategy is developed in naturally aspirated engine LCV application to meet cycle emissions, real drive emissions and OBD requirements.

The increasing demand for higher specific power, fuel economy, Operating Costs as well as meeting global emission norms have become the driving factors of today’s product development in the automotive market. Substitution of high-density materials and more precise adjustment of material parameters help in significant weight decrease, but it is accompanied by undesirable cost increase and manufacturing complexity. This becomes a challenge for every automotive engineer to balance the above parameters to make a highly competitive design. This work is a part of the Design and Development of 2.2 L, 4 Cylinder TCIC Diesel Engine for a whole new vehicle platform, concentrated on automotive passenger car operation. This paper explains the selection of a suitable cylinder head gasket technology for a lightweight engine that acts as a sealing interface between the cylinder block and cylinder head.

Mechanical control cables or Bowden cables are widely used in various applications for push-pull actions of mechanical systems. In mid-segment tractors, the linkage systems are designed along with control cables to actuate controls such as throttle, braking, transmission shift, position control, etc. due to its design flexibility. Output force and travel efficiency are two major performance parameters that depend on the routing, cable design composition, friction material, load transfer, etc. Virtual simulations can be used to predict cable performance and efficiency. There are different methodologies currently used to model the cable. These available methods can accurately predict either performance or travel efficiency. There is no method available in-house to predict both these parameters. In this paper, a new cable modeling method is proposed by authors using multi-body simulation (MBS) software MSC ADAMS.

Attaining better acoustic performance and back-pressure is a continuous research area in the design and development of passenger vehicle exhaust system. Design parameters such as tail pipe, resonator, internal pipes and baffles, muffler dimensions, number of flow reversals, perforated holes size and number etc. govern the muffler design. However, the analysis on the flow directivity from tail pipe is limited. A case study is demonstrated in this work on the development of automotive muffler with due consideration of back pressure and flow directivity from tail pipe. CFD methodology is engaged to evaluate the back pressure of different muffler configurations. The experimental and numerical results of backpressure have been validated. The numerical results are in close agreement with experimental results.

Internal combustion engine vehicles are major contributors to many environmental and health hazardous emissions and sometimes consume more fuel. New regulations like Corporate Average Fuel Efficiency (CAFÉ) norms are coming up and demand lower emissions. Original Equipment Manufacturers (OEMs) are committed to bringing various technological advancements in Internal Combustion Engine (ICE)powered vehicles to maximize their efficiency. Hence it is important to reduce the loss and improve the fuel economy. This paper explains a new approach methodology used for reducing the gearbox drag by 5- 10 %. This improvement can significantly contribute to the overall efficiency improvement thus carbon footprints of vehicle getting reduced.

The global automotive industry is growing rapidly in recent years and the market competition has increased drastically. There is a high demand for passenger car segment vehicles with high torque delivery and fuel economy for a pleasant drivability experience. Also, to meet the more stringent emission requirements, automakers are trying very hard to reduce the overall vehicle gross weight. In lowering both fuel consumption and CO2 generation, serious efforts have been made to reduce the overall engine weight. An engine cylinder block is generally considered to be the heaviest part within a complete engine and block alone accounts for 3-4% of the total weight of the average vehicle, thus playing a key role in weight reduction consideration. Aluminum casting alloys as a substitute for the traditional cast iron can mean a reduction in engine block weight between 40 and 55% [9], even if the lower strength of aluminum compared to grey cast iron is considered.

Original Equipment Manufacturers (OEMs) should innovate ways to delight customers by creating affordable products with improved drive experience and occupant comfort. Vehicle refinement is an important initiative that is often take-up by the project teams to ensure that the product meets the customer’s expectations. A few important aspects of vehicle refinement include improving the Noise Vibration Harshness (NVH), ride and handling performance pertaining to the Functional Image (FI) of the product. Optimizing the suspension design variables to meet both ride and handling performance is often challenging as improving the ride will have a deteriorating effect on handling and vice-versa. The present work involves Multi-Objective Design Optimization (MDO) of the suspension system of an automotive Sports Utility Vehicle (SUV) platform considering both ride and handling requirements, simultaneously.

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.

The major area in which the automotive manufacturers are working is to produce high-performance vehicles with lighter weight, higher fuel economy and lower emissions. In this regard, hollow camshafts are widely used in modern diesel and gasoline engines due to their inherent advantages of less rotational inertia, less friction, less weight and better design flexibility. However, the dynamic loads of chain system, valve train and fuel injection pump (if applicable) makes it challenging to design over-head hollow camshafts with the required factor of safety (FOS). In the present work, high-fidelity FE model of a hollow camshaft assembly is simulated to evaluate the structural performance for assembly loads, valve train operating loads, fuel injection pump loads and chain system loads. The investigation is carried out in a high power-density (70 kW/lit) 4-cylinder in-line diesel engine.

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.

In order to sustain in automobile industry, fuel economy and robustness are playing vital role in vehicle. Every gram of weight will have an impact on fuel economy, thus burning a hole in consumers pocket and contributing heavily to the carbon footprint. Composite material development plays important role in meeting the stringent self-imposed targets of the automotive manufacturers and light weighting is becoming a prime option for improving Fuel Economy. The main objective of this paper is to optimize the weight of the luggage lid floor and reduce its cost without compromising on the strength by changing the raw material and manufacturing process. This part is in trunk compartment of the vehicle. Main function of this part is to withstand the luggage load under various user loading patterns at varied temperature and while driving on different road conditions.

The Introduction of Corporate Average Fuel Economy (henceforth will be addressed as CAFE) regulations demand suitable technological upgrades to meet the significant increase in targets of vehicle fleet fuel economy. Engine Downsizing and Friction Reduction measures help in getting one step closer to the target. In a Conventional Oil Pump, the pump discharge flow and pressure are a direct function of operating speed. There is no control over lubricant flow which results in increased power and fuel consumption due to its unnecessary pumping characteristics irrespective of the actual engine demand. This paper discusses the introduction of a variable displacement oil pump (henceforth will be addressed as VDOP) that was adapted to a 1.5-liter 3 Cylinder Diesel Engine. This approach helps the system to reduce parasitic losses as the oil flow is regulated based on the mechanical needs of the engine. The flow is regulated with help of a solenoid valve which receives input from the ECU.

Accurate ride and handling prediction is an important requirement in today's automobile industry. To achieve the same, it is imperative to have a good estimation of damper model. Conventional methods used for modelling complex vehicle components (like bushings and dampers) are often inadequate to represent behaviour over wide frequency ranges and/or different amplitudes. This is difficult in the part of OEMs to model the physics-based model as the damper’s geometry, material and characteristics property is proprietary to part manufacturer. This is also usually difficult to obtain as a typical data acquisition exercise takes lots of time, cost, and effort. This paper aims to address this problem by predicting the damper force accurately at different velocity/ frequency and amplitude of measured data using Artificial Neural Networks (ANN).

Suspension plays a crucial role in stabilizing, comfort and performance of a vehicle. During vehicle braking operation, load transfer happens from rear axle to front axle resulting in shifting of vehicle’s center of gravity towards vehicle front for a momentarily duration which is called diving. This phenomenon leads to dropping of traction at rear wheel end resulting in lifting of rear axle with front wheel as pivot. This causes increase in front to rear weight ratio of vehicle system and compromising driver safety due to skidding and locking of rear wheel-end. To minimize this phenomenon’s affect, optimum anti-dive suspension geometry is used to have better rear wheel end traction resulting in improved braking stability.

In today’s scenario, internal combustion engines have conflicting requirements of high power density and best in class weight. High power density leads to higher loads on engine components and calls for a material addition to meet the durability targets. Lightweight design not only helps to improve fuel economy but also reduces the overall cost of the engine. Material change from cast iron to aluminium has a huge potential for weight reduction as aluminium has 62% lesser mass density. But this light-weighting impacts the stiffness of the parts as elastic modulus drops by around 50%. Hence, this calls for revisiting the design and usage of optimization tools for load-bearing members on the engine to arrive at optimized sections and ribbing profiles. This paper discusses the optimization approach for one of the engine components i.e., the FEAD (front end accessory drive) bracket.