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Error in suspension asymmetry or tire parameters may lead to vehicle drifting laterally from its intended straight-line path, which is called vehicle pull. Driver then needs to apply constant steering correction to maintain the vehicle in straight line which will lead to high driver fatigue and deteriorate driving experience. Manufacturing a perfectly symmetric suspension system is impractical, however an insight into the manufacturing tolerances of suspension system at the early design stage can be extremely useful. Also tire force and moment parameters at straight line operation and its maximum allowable variations will help in defining the tire parameter specifications and tolerances. The objective of this study was to develop a 1D model of suspension and tire system which can predict the torque experienced in steering and drift of the vehicle from straight line due to the tire force and moment and asymmetric suspension geometry.

The vehicle Heating, Ventilation and Air conditioning (HVAC) system is designed to meet both the safety and thermal comfort requirements of the passengers inside the cabin. The thermal comfort requirement, however, is highly subjective and is usually met objectively by carrying out time dependent mapping of parameters like the velocity and temperature at various in-cabin locations. These target parameters are simulated for the vehicle interior for a case of hot soaking and its subsequent cool-down to test the efficacy of the AC system. Typically, AC performance is judged by air temperature at passenger locations, thermal comfort estimation along with time to reach comfortable condition for human. Simulating long transient vehicle cabin for thermal comfort evaluation is computationally expensive and involves complex cabin material modelling.

This paper addresses challenges in current Fuel Cell Stack Buses and presents a novel Fuel Cell Electric Vehicle Bus (FCEV-Bus) powertrain that combines fuel cells, ultra-capacitors, and batteries to enhance performance and reliability. Existing Fuel Cell Stack Buses struggle with responsiveness, power fluctuations, and cost-efficiency. The FCEV-Bus powertrain uses a Fuel Cell stack as the primary power source, ultra-capacitors for quick power response, and batteries for addressing power variations. Batteries also save costs in certain cases. This combination optimizes power management, improves system efficiency, and extends the FCEV-Bus's operational life. In conclusion, this paper offers an innovative solution to overcome traditional fuel cell system limitations, making FCEV-Buses more efficient and reliable for potential wider adoption.

DFSS is a disciplined problem prevention approach which helps in achieving the most optimum design solution and provides improved and cost effective quality products. This paper presents the implementation of DFSS method to design a distinctive cooling system where engine is mounted in the rear and radiator is mounted in the front of the car. In automobile design, a rear-engine design layout places the engine at the rear of the vehicle. This layout is mainly found in small, entry level cars and light commercial vehicles chosen for three reasons - packaging, traction, and ease of manufacturing. In conventional Passenger cars, a radiator is located close to the engine for simple packaging and efficient thermal management. This paper is about designing a distinctive cooling system of a car having rear mounted engine and front mounted radiator.

Authors were challenged with a task of developing a full vehicle simulation model, with a target to simulate the electrical system performance and perform digital tests like Battery Charge Balance, in addition to the fuel efficiency estimation. A vehicle is a complicated problem or domain to model, due to the complexities of subsystems. Even more difficult task is to have a control algorithm which controls the vehicle model with the required control signals to follow the test specification. Particularly, simulating the control of a vehicle with a manual transmission is complicated due to many associated control signals (Throttle, Brake and Clutch) and interruptions like gear changes. In this paper, the development of a full vehicle model aimed at the assessment of electrical system performance of the vehicle is discussed in brief.

Reduction of NOx (Oxides of Nitrogen) and particulates from engine exhaust is one of the prime considerations in current research and development in automotive industry. The present paper describes the combustion optimization done on a four cylinder, 4 liter DI diesel engine to meet stringent Euro-III emission norms. The engine FIE (Fuel Injection Equipment) and injector geometry was optimized for performance and emission. Smoke measurements were considered as indicative of soot, to predict particulate emissions. This was done to simplify the overall process and save development time. It was concluded that by combining the flexibility of electronically controlled fuel injection begin, with improved nozzle technologies, with higher spray velocities and spray penetration, a considerable reduction in NOx and particulate emissions can be achieved. This can serve as a low cost solution, without any exhaust after-treatment systems.

In developing nations, most passenger vehicles are equipped with mobile air conditioning (MAC) systems that work on Hydro Fluoro Carbons (HFC) based refrigerants. These refrigerants have a high global warming potential (GWP) and hence adversely affect the environment. According to the Kigali amendment to Montreal Protocol, Article-5 Group-2 countries including India must start phasing down HFCs from 2028 and replace them with low Global Warming Potential (GWP) refrigerants. One such class of low GWP refrigerant is Hydro Fluoro Olefins (HFO) In order to replace HFCs with HFOs in existing MAC systems, the various system performance parameters with the new refrigerant are required to be evaluated. Performance evaluation of MAC system is rendered quicker and cost-effective by deploying a digital simulation tool. There is good correlation and confidence established for MAC performance prediction with HFCs through 1D CAE.

With India achieving the BSVI milestone, the diesel particulate filter (DPF) has become an imperative component of a modern diesel engine. A DPF system is a device designed to trap soot from exhaust gas of the diesel engine and demands periodic regeneration events to oxidize the accumulated soot particles. The regeneration event is triggered either based on the soot mass limit of the filter or the delta pressure across it. For a Heavy Duty Diesel Engine (HDDE), pressure difference across the DPF is not usually reliable as the size of the DPF is large enough compared to the DPF used ina passenger vehicle diesel engine. Also, the pressure difference across DPF is a function of exhaust mass flow and thus it makes it difficult to make an accurate call for active regeneration. This demands for a very accurate soot estimation model and it plays a vital role in a successful regeneration event.

Micro Hybrid Systems are a premier approach for improving fuel efficiency and reducing emissions, by improving the efficiency of electrical energy generation, storage, distribution and consumption, yet with lower costs associated with development and implementation. However, significant efforts are required while implementing micro hybrid systems, arising out of components like Intelligent Battery Sensor (IBS). IBS provides battery measurements and battery status, and in addition mission critical diagnostic data on a communication line to micro hybrid controller. However, this set of data from IBS is not available instantly after its initialization, as it enters into a lengthy learning phase, where it learns the battery parameters, before it gives the required data on the communication line. This learning period spans from 3 to 8 hours, until the IBS is fully functional and is capable of supporting the system functionalities.

On Board Diagnostics norms enforced by regulatory authorities of many countries require logging of distance traveled by the vehicle with MIL (malfunction indicator lamp) illuminated. This log needs to be maintained in non-volatile ECU memory. Conventional techniques maintain the log in a volatile memory during vehicle run-time and transfer the same to non-volatile memory when ignition is turned off. This requires use of a “power-hold” relay to keep an ECU power alive while the logged data in volatile memory is being transferred to non-volatile memory when ignition is switched-off. A novel strategy described in this paper avoids interface with power-hold relay, thereby reducing the system complexity. The design philosophy described makes use of an EEPROM to maintain the distance log. An innovative algorithm is employed to ensure that endurance specifications are not violated during the vehicle life-time.

This paper aims at analysing the effect of regeneration braking on the amount of energy harnessed during vehicle braking, coasting and its effect on the drive train components like gear, crown wheel pinion, spider gear & bearing etc. Regenerative braking systems (RBS) is an effective method of recovering the kinetic energy of the vehicle during braking condition and using this to recharge the batteries. In Battery Electric Vehicles (BEV), this harnessed energy is used for controlled charging of the high voltage batteries which will help in increasing the vehicle range eventually. Depending on the type of the powertrain architecture, components between motor output to the wheels will vary, i.e., in an e-axle, motor is coupled with a gear box which will be connected with differential and the wheels. Whereas in case of a central drive architecture, motor is coupled with gearbox which is connected with a propeller shaft and then the differential and to the wheels.

Computer Aided Engineering (CAE) plays an important role in the product development. Now a days major decisions like concept selection and design sign off are taken based on CAE. All the Original Equipment Manufacturers (OEMs) are putting consistent efforts to improve accuracy of the CAE results. In recent years confidence on CAE prediction has been increased mainly because of good correlation of CAE predictions with the test results. Defining proper correlation criteria and using a systematic approach helps significantly in building the overall confidence level for predictions given by CAE simulations. Representation of manufacturing effects on material properties and material failure in the simulation is still a big challenge for achieving a good CAE correlation. This paper describes side impact test vs CAE correlation. The important parameters affecting the CAE correlation were discussed.

Adaption of EV powertrains in existing vehicle architecture has created many unique challenges in meeting performance, reliability, safety, ease of manufacturing & serviceability at optimum cost. Mounting of large size battery packs in existing vehicle architecture is one of them. Specific energy & the energy density of Lithium ion batteries are very lower compared to Diesel & Petrol, which requires high volume & weight for equivalent energy storage. For movement of many passengers and to ensure sufficient range EV buses typically needs large amount of energy and for storage of same bigger size battery packs are required. These large size batteries directly affect vehicle architecture, seating layout, ease of assembly & serviceability. Moreover the heavy mass of batteries directly influences vehicle dynamics & performance characteristics such as vehicle handling, roll & NVH. The most important consideration in design of EV vehicles in general and buses in specific is safety.

Structural adhesive is a good alternative to provide required strength at joinery of similar and dissimilar materials. Adhesive joinery plays a critical role to maintain structural integrity during vehicle crash scenario. Robust adhesive failure definitions are critical for accurate predictions of structural performance in crash Computer Aided Engineering (CAE) simulations. In this paper, structural adhesive material characterization challenges like comprehensive In-house testing and CAE correlation aspects are discussed. Considering the crash loading complexity, test plan is devised for identification of strength and failure characteristics at 0°, 45°, 75°, 90°, and Peel loading conditions. Coupon level test samples were prepared with high temperature curing of structural adhesive along with metal panels. Test fixtures were prepared to carryout testing using Instron VHS machine under quasi-static and dynamic loading.

Steering pull during high speed braking of heavy commercial vehicles possesses a potential danger to the occupants. Even with negligible wheel-to-wheel brake torque variation, steering pull during the high speed braking has been observed. If the steering pull (i.e. steering rotation) is forcibly held at zero degree during high speed braking, the phenomena called axle twist, wheel turn and shock absorber deflection arise. In this work the data have been collected on the mentioned measures with an intention to develop a mathematical model which uses real time data, coming from feedback mechanism to predict the values of the measures in coming moments in order to aid steering system to ‘auto-correct’. Driven by the intention, ‘Time Series Analysis’, a well-known statistical methodology, has been explored to see how suitable it is in building the kind of model.

Engine Stop/Start System (ESS) promises to reduce greenhouse emissions and improve fuel economy of vehicles. Previous work of the Authors was concentrated on bridging the gap of improvement in fuel economy promised by ESS under standard laboratory conditions and actual driving conditions. Findings from the practical studies lead to a conclusion that ESS is not so popular among the customers, due to the complexities of the system operation and poor integration of the system design with the driver behavior. In addition, due to various functional safety requirements, and traffic conditions, actual benefits of ESS are reduced. A modified control algorithm was proposed and proven for the local driving conditions in India. The ways in which a given driver behaves on the controls of the vehicles like Clutch and Brake Pedals, Gear Shift Lever were not uniform across the demography of study and varied significantly.

With the current state of ever rising fuel prices and unavailability of affordable alternate technologies, significant research and development efforts have been invested in recent times towards improving fuel efficiency of vehicles powered with conventional internal combustion engines. To achieve this, a varied approach has been adopted by researchers to cover the entire energy chain including fuel quality, combustion quality, power generation efficiency, down-sizing, power consumption efficiency, etc. Apart from energy generation, distribution and consumption, another domain that has been subjected to significant scrutiny is energy recuperation or recovery. A moving vehicle and a running engine provide a number of opportunities for useful back-recovery and storage of energy. The most significant sources for recuperation are the kinetic energy of the moving vehicle or running engine and to a lesser extent the thermal energy from medium such as exhaust gas.

An analytical model, which takes care of thermal interactions of human body with surroundings via basic heat transfer modes like conduction, convection, radiation and evaporation, is compiled. The analytical model takes measurable inputs from surroundings and specific human parameters. Using these parameters a quick calculation entailing all heat transfer modes ensues in net heat exchange of human body with surroundings. Its magnitude and direction decides the qualitative indication of thermal comfort of concerned human being. The present model is scaled on actual human beings by noting the subjective assessment in comfortable as well as uncomfortable surroundings. As a part of validation, it is implemented in an actual Climatic Wind Tunnel Heater test, where temperatures and other parameters on different parts of the body are noted down and fed to the model as input. Output of the equation is then compared with the subjective assessment of human beings.

In high-end commercial vehicles, technologies like Electronic Braking Systems (EBS) help pull away the vehicle from a standstill on steep gradients with no risk of rolling back. Tata Motors has developed an indigenous Anti-Roll Back (ARB) system that effectively minimizes this risk but without the use of EBS/HSA. The ARB delivers identical functionality to the HSA feature in the EBS but autonomously, and by purely electric means. In the proposed system, the electric traction motor develops a high positive torque when the vehicle tries to roll back upon minimal accelerator pedal press. The system is autonomous in the sense that the driver does not need to press any HSA switch on the dashboard and the system works on relatively flatter road also which otherwise is not the case with HSA as it negatively affects the operation on flatter road by locking wheels and vehicle launches with a very high torque when brakes are automatically released by EBS upon threshold torque build-up.

When an automobile negotiates a flooded region, water is splashed due to the rotational motion of the wheels. This water enters the air intake system of the turbocharged intercooled engine along with air and can pass through the turbocharger, intercooler and enter the engine. As water is an incompressible fluid, the piston cannot compress water inside the cylinder which leads to connecting rod bending and severe engine damage. This paper explains how the same has been resolved using CFD methodology and proposes the re-designed model of mud cover as a solution to this problem. The entire process has been streamlined and major time and cost reduction achieved by using simulation for optimization. The simulated results have been validated by extensive trials for correlation and outdoor tests for durability. Same analysis technique is used as a template to modify the air intake system.