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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.

There has to be a good co-relation/ relationship between the pedal effort applied, pedal travel, deceleration level achieved and stopping distance for “good brake feel”. Brake feel also depend upon the time lag between the force applied on brake pedal and the response of braking system. Hence “brake feel” can be improved by reducing the response time of the brake system. Many vehicles are having “poor brake feel” complaints, pertaining to the above mentioned reasons. This paper relates to an improved brake system for automobile in which reduction in reaction time was done by artificially increasing differential pressure head across vacuum booster diaphragm. Brake booster is given an input of compressed air to the valve body during actuation, thereby increasing the differential pressure across the diaphragm. The compressed air is bled from turbocharger-intercooler of the vehicle which is stored in a reservoir, with one way valve, while cruising.

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.

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.

This paper proposes a cost effective method, with simple techniques, to evaluate Bump Steer and Brake Steer on a rigid axle vehicle under dynamic conditions. A relationship between calculated values, measured values and a subjective assessment of the vehicle lateral deviation is established. An array, of inter-relationship of the parameters such as offset of steering arm, draglink length, front spring stiffness, height of spring hanger bracket is done. Percentage of influence of the parameter change on the performance of the vehicle is evaluated and standard statistical analysis is used to arrive at inter-relationship of various parameters and ranking of their influence on lateral deviation of the vehicle under braking is established, there by resulting in reduction in iterative process. The results obtained display a good correlation with ADAMS Analysis to the tune of 90% and are in agreement with subjective assessment.

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.

ISOFIX anchorage plays a critical role in restraining child occupants during crashes. Effective design of ISOFIX anchorages is essential for achieving controlled child occupant kinematics. CAE simulations are extensively used for the development of ISOFIX anchorages. Comprehensive material characterization of ISOFIX wires play a vital role for achieving desired prediction accuracy. This paper covers the detailed process of ISOFIX material characterization for material failure prediction. ISOFIX wires are case hardened to exhibit required strength characteristics. Due to its material characteristics, the conventional material models don't give desired prediction accuracy for failure prediction. Therefore, advanced material models are developed in LS Dyna environment, which can accurately predict plastic and fracture behavior of ISOFIX wires.

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.

Diesel engines tend to operate on lower exhaust temperatures, compared to their gasoline counterparts. Exhaust emission control becomes a significant issue at these lower temperatures, as any catalytic converter needs certain light off temperature to commence functioning. The trend so far has been to move the catalytic converters closer to the exhaust manifold, in order to get the benefit of higher temperatures - but most of the applications are limited to the location available after the turbo chargers. This is due the fact that very minute and efficient catalyst is required, if it has to be placed before the turbo charger. This catalyst also needs to be extremely durable to take care of high exotherms which occur within the catalysts and also to prevent any possible damage to the turbo chargers.

The automotive industry is heading in the direction of signing off the exhaust system durability based on computer simulation rather than rig simulation and physical vehicle testing. This is due to the cost, time and availability of prototype vehicles and test track. Use of Finite Element Method (FEM) enables to assure the structural integrity of the exhaust system and also contribute to better understanding of the system behavior in the various operating conditions and evaluation of structural strength. This paper deals with dynamic analysis of a modular automotive exhaust system where it is directly mounted on power train pack. Selection of dynamic loads, processing of the test data, and effect of assembly loads along with material property variation due to temperature are explained. It also includes validation of the CAE model, prediction of probable failure locations and improving the design based on analysis outcome.

Better ride and comfort, enhanced safety, reliability and durability, lower running cost as well as cost of ownership continue to be challenges for automotive OEMs. Higher fuel efficiency is considered as USP not only for lower running cost but also is hygiene factor from sustainability point of view. This has necessitated the need for Augmenting Light weighting horizon in automotive OEMs. Augmenting this leads to invention of innovative materials and processes for emerging cost competitive market. This paper focuses on technology efforts towards augmenting light weighting Horizon in Automotive. Light weighting concepts being explored by OEMs with the help of automotive component manufacturers from Powertrain - Engines & Transmission, Chassis and Suspension are discussed.