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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.

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 BS6 norms (phase 1) were implemented in India from April 1, 2020 and replaced the previous BS4 norms. Phase 2 of the BS6 norms, which came into effect on April 1, 2023. In accordance with the regulation requirement, effective performance of after treatment systems like DPF and SCR demands critical hardware implementation and robust monitoring strategies in the extended operating zone. Effective OBD monitoring of DPF, which is common to all BSVI certified vehicles, such that the defined strategy detects the presence or absence of the component is imperative. A robust monitoring strategy is developed to detect the presence of the DPF in the real world incorporating the worst possible driving conditions including idling, and irrespective of other environmental factors subject to a location or terrain. The differential pressure sensor across the DPF is used to study the actual pressure drop across the DPF.

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.

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.

Electric Vehicle is the need of an hour, as due to excessive usage of IC Engine vehicles has resulted in the depletion of the ozone layer to a significant level and fuel cost is increasing. With new technologies coming into the market, challenges come hand in hand because of Electric Vehicle. In comparison to IC Vehicle, areas of thermal management or the number of components for which thermal management needs to be done is higher and rather complex. As the thermal management system is the second highest energy consuming source after the powertrain of the electric vehicle, an efficient and reliable design is mandatory to ensure better range in an Electric Vehicle. Thermal Management of the Electric Vehicle has been identified as one of the critical parameters for balancing both cabin comfort as well as Battery temperature. One of the major concerns is meeting the Cabin comfort during colder weather with minimum energy consumption.

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.

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.

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 the automotive industry the requirement for low emissions has led to the demand for lightweight vehicle structures. Light weighting can be achieved through different iterative approaches but is usually time consuming. Current paper highlights deployment of the multi-loadcase optimization approach for light weighting. This work involves developing a process for multiple loadcase optimization for automotive hood. The main goal is to minimize the weight of a hood assembly by meeting strength and stiffness targets. The design variables considered in this study are thickness of the panels. Design constraints were set for stress and stiffness based on DVP (Design Verification Plan) requirement. Optimization workflow is setup in mode-frontier with design objective of minimizing weight of hood.

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.

Aerodynamics of on-road vehicles has come to the limelight in the recent years. Better aerodynamic design of vehicle would improve vehicle fuel efficiency with increased acceleration performance. To obtain best aerodynamic body, the series of design modifications and different testing methodologies must be involved in vehicle design and validation phase. Wind tunnel aerodynamic force measurement, road load determination and computational fluid dynamics were the common methods used to evaluate the aerodynamic behavior of the vehicle body. As a novel approach, the present work discusses about the on-road (Real time) testing methodology that is aimed to evaluate the aerodynamic performance of vehicle body using surface pressure mapping. A 64-Channel digital pressure scanner has been utilized in this work for mapping the pressure at different locations of the typical vehicle body.

With the increase in the number of automobiles on road, there is a very strong emphasis on reducing the air pollution which led to evolution of stringent emission norms. To meet these stringent emission norms, the ideal solution is to optimize the engine hardware and the combustion system to reduce the emission at source thereby reducing the dependency on exhaust after treatment system. Gasoline Direct Injection (GDI) engines are gaining popularity worldwide as they provide a balance between fun to drive and fuel efficiency. Controlling the particle emissions especially Particle Number (PN) is a challenge in GDI engines due to the nature of its combustion system. In this study, experiments were performed on a 1.2Litre 3-cylinder 250bar GDI engine to capture the effect of injection strategies on PN.

This paper discusses the development of an all speed governed diesel-natural gas dual fuel engine for agricultural farm tractor. A 45 hp, 2.9 liters diesel-natural gas dual fuel engine with a novel closed loop secondary fuel injection system was developed. A frugal approach without any modification of the base mechanical diesel fuel injection system was followed. This approach helped to minimize the cost impact, while meeting performance and emissions at par with neat diesel operation. Additional cost on gas injection system is redeemed by cost savings on diesel fuel. The dual fuel technology developed by Mahindra & Mahindra Ltd., substitutes on an average approximately 40% of diesel with compressed natural gas, meeting the TREM III A emission norms for dual fuel while meeting all application requirements. The governing performance of the tractor was found to be superior than base diesel tractor.

Being a safety critical aggregate, every aspect of brake system is considered significant in vehicles operations. Along with optimum performance of brake system in terms of deceleration generation, brake pedal feel or brake feel is considered as one of the key elements while evaluating brake system of vehicles. There are many factors such as liner and drum condition, road surface, friction between linkages which impress the pedal feel. Out of these, in this paper we will be discussing the factors which influence the brake pedal feel in relation to the driver comfort and confidence building. Under optimum braking condition, brake operation must be completed with pedal effort not very less or not very high, brake pedal feel must be firm throughout the operation, in such a way that it will not create fatigue and at the same time it will give enough confidence to the driver while operating with acceptable travel.

Fuel efficiency is critical aspect for commercial vehicles as fuel is major part of operational costs. To complicate scenario further, fuel efficiency testing, unlike in passenger cars is more time consuming and laborious. Thus, to save on development cost and save time in actual testing, simulations plays crucial role. Typically, actual vehicle speed and gear usage is captured using reference vehicle in desired route and used it for simulation of target vehicle. Limitation to this approach is captured duty cycle is specific to powertrain and driver behavior of reference vehicle. Any change in powertrain or vehicle resistance or driver of target vehicle will alter duty cycle and hence duty cycle of reference vehicle is no more valid for simulation assessment. This paper demonstrates approach which uses combination of tools to address this challenge. Simulation approach proposed here have three parts.

The present work discusses the developed simulation model aimed to predict the heat rejection (HR) performance and external pressure drop characteristics of automotive charge air cooler (CAC). Heat rejection and airside pressure drop characteristics of CAC were predicted for the conditions of different charge air mass flow rates and different cooling air velocities. The lack of detailed research on CAC performance prediction has motivated the development of the proposed simulation model. The present 1-D simulation has been developed based on the signal library of AMESIM application tool. Input parameters for this simulation such as core size, tube pitch, tube height, number of tubes, fin density, louver angle, louver pitch, charge air mass flow rate, cooling air velocity, charge air inlet temperature, and ambient temperature. Heat rejection curve and airside pressure drop of CAC were the output of the present simulation.

It is imperative that all automobile manufacturers conduct vehicle level benchmarking at the initial stage of any new project. From the benchmark information, the manufacturers can set relevant targets for their own vehicles under development. In this regard, an accurate prediction of the engine operating points can improve the correlation of the measured fuel economy of the benchmark vehicle. The present work describes a novel method that can be used for the accurate prediction of the engine operating points of any benchmark vehicle. Since the idea of instrumenting the crankshaft/driveshaft with torque transducers is a costlier and time-consuming process, the proposed method can be effective in reducing the benchmarking. Hence, the objective of this work is to develop a mathematical model to calculate the real-time engine operating points (engine speed and torque) using parameters like vehicle speed, accelerator pedal map, driveline inertia, vehicle coastdown force and gradient.

Major focus was given on the Comfort, Fuel efficiency & Safety during the development of the passenger cars, which certainly drives the vehicle business of Original Equipment Manufacturer (OEM’s). The air Conditioning in a car, plays an important role in the area of comfort of the passengers and fuel efficiency point of view. Especially Heat Exchanger plays a pivotal role in the air conditioning system. So, it’s a challenge for the OEM’s to select and design the optimal heat exchanger from the supplier, which meets the performance and packaging requirements during the design phase of the product development cycle. The objective of this paper to focus on analytical calculation or framework was developed using an excel tool considering the effect of variable geometry of fin which includes louver pitch, louver angle and louver length in a multi-pass condenser. Further, this theoretical calculation was validated using experimental data and CFD simulation.