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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.

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].

Automakers are being subjected to increasingly strict fuel economy requirements which led OEMs to focus more on Light weighting and Energy efficiency areas. Considering the aforesaid challenges, efforts have been taken in Light weighting of mounting bracket for Engine application. This paper deals with conversion of Engine accessory bracket from Aluminum material to Metal Matrix composite (MMC). In Design phase, existing bracket has been studied for its structural requirements and further Bracket is designed to meet MMC process requirement and CAE carried out for topology optimization and Structural integrity. Finally observations and results were compared for Existing design and Proposed design and further optimization proposed.

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.

Vehicle dynamics is one of the most important vehicle attributes. It is classified into three domains, the longitudinal, vertical, and lateral dynamics. This paper focuses on optimizing the lateral vehicle dynamics which is driven by the straight ahead controllability and cornering controllability of the vehicle. One of the important parameters that dictates these sub-attributes is the steering ratio. Therefore, designing the right steering ratio is critical to meet the vehicle “specific” targets. Significant amount of work has been done by many researchers on variable steering ratio by implementing variable gear ratio (VGR) rack, active steering, and steer-by-wire systems. This paper discusses the methodology and considerations to optimize the steering ratio for a constant gear ratio rack by optimizing the steering column layout, viz., orientation and the phase angle in universal joints.

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.

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.

Structural optimization has evolved vastly based on the development of computational based analysis – CAE. Structural optimization is usually a linear static response optimization because nonlinear response structural optimization is very expensive to perform. But in the real world, most of the automobile load cases are non-linear in nature. Equivalent static load structural optimization is a structural optimization method where Equivalent Static Loads (ESLs) are utilized as external loads for linear static response optimization. ESL is defined as the static load that generates the similar displacement by an analysis which is not linear static. This paper explains the development of a weight optimized BIW structure from an already existing model satisfying the NVH and Crash requirements. Basic structural crash loads are converted into ESLs with appropriate constraints.

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.

The jet lubrication method is extensively used in the constant mesh high performance transmission system operating at range of speeds though it affects mechanical efficiency through spin power loss. The lubrication jet has a key role to maintain the meshing gears at non-fatal thermal equilibrium by effectively dissipating the heat generated to the surrounding. Heat transfer coefficient (HTC) is the indicator of the thermal behavior of the system, which provides great insight of efficient lubrication system that needs to be employed for prescribed type of transmission. In this study, a segment of the transmission unit which constitutes a gear pair is used for the simulation. Parametric study is carried out by considering the critical parameters affecting the thermal performance such as lubrication jet flow rate and rotational motions of the gears with speeds and temperatures.

During cabin warm-up, effective air distribution by vehicle climate control systems plays a vital role. For adequate visibility to the driver, major portion of the air is required to be delivered through the defrost center ducts to clear the windshield. HVAC unit deliver hot air with help of cabin heater and PTC heater. When hot air interacts with cold windshield it causes thermal losses, and windshield act as sink. This process may causes in delay of cabin warming during consecutive cabin warming process. Thus it becomes essential to predict the effect of different windscreen defrost characteristics. In this paper, sensitivity analysis is carried for different windscreen defrosts characteristics like ambient conditions, modes of operation; change in material properties along with occupant thermal comfort is predicted. An integrated 1D/3D CFD approach is proposed to evaluate these conditions.

Fatigue life predictions using the strain-life method are used in the design of modern light weight vehicle, for the complex loading that occur with the structural durability tests that these vehicles undergo. The accuracy of these predictions is dependent upon the many factors; geometry, loads & materials etc. This paper details a new procedure to ensure the quality and accuracy of the material parameters for the fatigue life prediction software. The material parameters for the solver are obtained by performing strain-controlled fatigue tests. The geometry of the coupons tested is determined by size and thickness of the material specimen that they are machined from and the loading regime in the test. Detailed data analyzed is conducted on these tests and the parameters that are used as input into the CAE strain-life fatigue prediction software are generated.

The unit analysis methodology can be used for designing component or product in a product development process. This method may be used for designing the crush can, bumper beam, crush can long member, B-frame or A-pillar in frontal impact analysis. Unit assembly model technique can be effectively used in many CAE load cases to evaluate CAE simulations such as pedestrian impact analysis (ECE R78 / ENCAP), interior trim related head impact simulations (FMVSS201U), under run protection simulation for commercial vehicles (Front Underrun Protection Device ECE R93, Rear Underrun Protection Device ECE R58, Side Underrun Protection Device ECE R73), airbag deployment optimization etc. These CAE analyses correlate better with actual test. This paper gives idea about how the cost of product design can be reduced by using unit analysis. To reduce time of vehicle development such as cost of prototype, testing cost, optimization cost unit analysis is more economical.

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.

Progress in material research is the driving force behind innovative ideas and characterising the newly invented material accurately is need of the hour. Increased use of polymers in automobile industry has led to the need for accurately capturing polymer material properties. In case of polymers, we generally observe negative slope in true stress strain curves due to inherent material behaviour. It is mainly because of polymer chains which realign/untangle in the direction of load. This is a challenge when we characterise polymers material properties to be used in LS_DYNA software, which is widely used in automotive applications to solve dynamic crash events. This software does not allow negative slope in stress strain curves in the plastic region and that causes model instabilities. This paper explains the methodology to avoid negative slope and still characterise the polymers without significantly loosing on the accuracy and correlation to physical tests.

Hardware-in-the-Loop (HIL) simulation is a technique used extensively in the development and testing of complex real-time embedded systems. Most of the HILs built around the world focus on specific part of a vehicle. This paper describes an in house HIL system developed for the complete hybrid car. In this HIL, the focus was to have HIL based on open hardware which is low cost and modular. It is customizable as per complex interdisciplinary vehicle requirements from Original Equipment Manufacturer that reduces dependency on suppliers and allows testing in an integrated vehicle environment. Code for operating HIL is developed in house. This HIL allows engineers to access ECU and plant model simultaneously and generate test report automatically. It consists of a vehicle plant model developed using MathWorks® Tool chain-MATLAB and Simulink. FPGA Plugin consist of software implementation of vehicle sensors in LabVIEW™ software from National Instruments (NI).

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.

In a Mild hybrid electric vehicle, a battery serves as a continuous source of energy but is inefficient in supplying peak power demands required during torque assists for short duration. Moreover, the random charging and discharging that result due to varying drive cycle of the vehicle affects the life of the battery. In this paper, an Ultra-capacitor based hybrid energy storage system (HESS) has been developed for mild hybrid vehicle which aims at utilizing the advantages of ultracapacitors by combining them with lead-acid batteries, to improve the overall performance of the battery, and to increase their useful life. Active current-sharing is achieved by interfacing ultracapacitor to the battery through a bi-directional boost dc-dc converter.

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.

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.