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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.

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.

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.

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.

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.

Battery Thermal management is a major challenge for occupant safety in an electric vehicle. Predicting the battery electrical losses and thermal behaviour is another challenge for the battery management system. Different virtual models are developed for cell level and pack level thermal evaluation. All these models have a varying degree of accuracy and limitation. The latest developed model is more accurate and can predict the battery cell & pack level temperatures. The battery can be modeled in different ways, ECM (Electrochemical model), EIS (Electrochemical Impedance Spectroscopy) [1]. Newman model is a well-known electrochemical model. [2]. EIS uses a combination of DC and small AC signal [3,4]. ECM model also used for estimating SOC and in BMS [5]. The cell temperature in the battery pack not only depends upon the cell inside physics but also depends upon cell outside cooling physics. Cell outside physics is simulated by 3D CFD software during the design process [6].

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.

The performance of door assembly is very significant for the vehicle design and door sag/set is one of the important attribute for design of door assembly. This paper provides an overview of conventional approach for door sag/set study based on door-hinge-BIW assembly (system level approach) and its limitation over new approach based on subassembly (subsystem level approach). The door sag/set simulation at system level is the most common approach adopted across auto industry. This approach evaluates only structural adequacy of door assembly system for sag load. To find key contributor for door sagging is always been time consuming task with conventional approach thus there is a delay in providing design enablers to meet the design target. New approach of door sag/set at “subsystem level” evaluates the structural stiffness contribution of individual subsystem. It support for setting up the target at subsystem level, which integrate and regulate the system level performance.

Electric vehicles (EVs) carries two main anxieties in users which are its range and battery life, hence these are important parameters to be taken care of during electric vehicle development. Range of EV depends on many parameters such as vehicle weight, heating ventilation and air conditioning (HVAC) system, battery cooling system (BCS), traction cooling system (TCS) and other electrical loads, which consumes power from a High Voltage (HV) battery. Severe hot ambient in India requires a big size HVAC system, on the other hand, the battery pack needs refrigerated cooling system to keep its temperature in control. Hence, the major parasitic consumers in an EV are HVAC and BCS. In order to enhance the overall efficiency, a trade-off between these two systems is crucial, as both the systems are served with common compressor and condenser in dual loop refrigerant circuit.

New noise regulations, with reduced noise limits, have been proposed by UN-ECE. A new method which aims at representing urban driving of the vehicles more closely on roads is proposed and is considerably different from the existing one (IS 3028:1998). It is more complex; we also found that some of the low powered vehicles can not be tested as per this method. The paper proposes ways of improvement in the test method. The new noise reduction policy options will have a considerable impact on compliance of many categories of vehicles. Technological challenges, before the manufacturers, to meet all performance needs of the vehicle along with the cost of development will be critical to meet the new noise limits in the proposed time frame.

This paper describes the Common Automobile Program (CAP) that can be implemented to improve mass transportation. CAP is the use of automated electric vehicles using smart navigation and control technologies to improve mass transportation. In CAP, common vehicles are used by different passengers, thus, reducing the on-road traffic and also the parking space required. Various low-cost stations are to be built along specified paths and the vehicle can be used at the convenience of the commuter. Currently, buses and trains require the passengers to wait at the station and a significant amount of time is spent at intermediate stops. The vehicle in CAP runs directly from origin to destination and also eliminates the waiting time at stations. Passengers do not wait for vehicles; instead vehicles wait for the passengers. The journey starts as the passenger enters the station and selects the destination.

Conventionally, the automotive outer panels, giving vehicle its shape, have been manufactured from steel sheets. The outer panels are subjected to loads due to wind loading, palm-prints, person leaning on the vehicle, cart hits, and hail stones for example. Consumer awareness about these two panel characteristics: Oilcanning and Dent resistance is increased, which has been observed in recent marketing studies. Apart from perceptive quality, another factor depending on the dent performance is insurance and respective cost implications. Dents can occur due to several reasons such as object hits, parking misjudgement, hail stones etc. Phenomenon can be divided into two types, static and dynamic denting. Static dent case covers scenario wherein interaction with outer panel is mostly quasi-static. Hail stones present dynamic case where object hits a panel with certain kinetic energy. Automotive companies usually perform static dent assessment to cover all the cases.

The vehicle crash signature (here on referred as crash pulse) significantly affects occupant restraints system performance in frontal crash events. Restraints system optimization is usually undertaken in later phase of product development. This leads to sub-optimal configurations and performance, as no opportunity exists to tune vehicle structure and occupant package layouts. In concept phase of development, crash pulse characterization helps to map occupant package environment with available structure crush space and stiffness. The crash pulse slope, peaks, average values at discrete time intervals, can be tuned considering library of restraints parameters. This would help to derive an optimal occupant kinematics and occupant-restraints interaction in crash event. A case study has been explained in this paper to highlight the methodology.

Engine cooling systems for vehicles are used for cooling the engine fluids. The cooling system normally consists of following components: radiator, expansion tank, cooling fan, fan drive and shroud. The mounting structure for this system must be designed to withstand the loads that will be imposed by the vehicle operation which consists of stresses such as those caused by linear static and dynamic loading. Automotive industries perform various tests on vehicles in the end-user environment to reduce failures; these investigations are carried out on the design using finite element method (FEM). Finite element methods are being used routinely to analyze for structural behavior. Modeling is done with CATIA software, meshing is carried out with HYPERMESH software and solution is acquired using NASTRAN solver.

Increasing demands on engine power to meet increased load carrying capacity and adherence to emission norms have necessitated the need to improve thermal management system of the vehicle. The efficiency of the vehicle cooling system strongly depends on the fan and fan-shroud design and, designing an optimum fan and fan-shroud has been a challenge for the designer. Computational Fluid Dynamics (CFD) techniques are being increasingly used to perform virtual tests to predict and optimize the performance of fan and fan-shroud assembly. However, these CFD based optimization are mostly based on a single performance parameter. In addition, the sequential choice of input parameters in such optimization exercise leads to a large number of CFD simulations that are required to optimize the performance over the complete range of design and operating envelope. As a result, the optimization is carried out over a limited range of design and operating envelope only.

The purpose of Federal Motor Vehicle Safety Standard 216 is to reduce fatalities and serious injuries when vehicle roof crushes into occupant compartment during rollover crash. Upgraded roof crush resistance standard (571.216a Standard No. 216a) requires vehicle to achieve maximum applied force of 3.0 times unloaded vehicle weight (UVW) on both driver and passenger sides of the roof. (For vehicles with gross vehicle weight rating ≤ 6,000 lb.) This paper provides an overview of current approach for dual side roof strength Finite Element Analysis (FEA) and its limitations. It also proposes a new approach based on powerful features available in virtual tools. In the current approach, passenger side loading follows driver side loading and requires two separate analyses before arriving at final assessment. In the proposed approach only one analysis suffices as driver and passenger side loadings are combined in a single analysis.

A number of market factors such as customer demand for improved connectivity and infotainment systems, automated driver assist systems and electrification of powertrain have driven an increase in the number of electrical systems within the cabin of automotive vehicles. These systems have limited operating temperature windows, therefore markets with high ambient temperatures and solar loading represent a significant challenge due to high cabin temperatures. Traditionally climatic facilities have been used replicate the conditions seen in these markets in order to understand the performance of the electrical systems. However such facilities have a number of limitations such as fixed solar arrays, secondary radiation from the walls and substantial operating costs limiting testing to envelope tests. Therefore the requirement for CAE based approach to more accurately represent the conditions seen in the real world is clear.

Underrun Protection devices (UPDs) are specially designed barriers fitted to the front, side, or rear of heavy trucks. In case of accidents, these devices prevent small vehicles such as bikes and passenger cars going underneath and thus minimizing the severity of such accident. Design and strength of UPD is such that it absorbs the impact energy and offers impact resistance to avoid the vehicle under run. Compliance to UPD safety regulations provides stringent requirements in terms of device design, dimensions, and its behavior under impact loading. Since accuracy of Computer Aided Engineering (CAE) predictions have improved, numerical tools like Finite element method (FEM) are extensively used for design, development, optimization, and performance verification with respect to target regulatory performance requirements. For improved accuracy of performance prediction through FEA, correct FE representation of sub-systems is very important.

Automotive OEMs are launching multiple products with ever reducing development time, balancing costs, quality and time to market, with clear focus on performance and weight. Platform architecture concepts, modular designs for differentiation etc. are strategies adopted by automotive OEMs towards shorter development cycles. Thus, concept generation phase of the digital product development process is expected to enable generation and evaluation of multiple concept architectures, carry out performance studies and largely focus on optimization, upfront. This Front loading of engineering and call for simultaneous engineering requires support in terms of quick and good CAD modeling with maturity. This paper proposes a process that focuses on generation and evaluation of multiple concepts, besides enabling optimization of concept before the detailed design phase kicks in.