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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].

In an environment of tougher engineering constraints to deliver tomorrow's aerodynamic vehicles, evaluation of aerodynamics early in the design process using digital prototypes and simulation tools has become more crucial for meeting cost and performance targets. Engineering needs have increased the demands on simulation software to provide robust solutions under a range of operating conditions and with detailed geometry representation. In this paper the application of simulation tools to wheel design in on-road operating conditions is explored. Typically, wheel and wheel cover design is investigated using physical tests very late in the development process, and requires costly testing of many sets of wheels in an on-road testing environment (either coast-down testing or a moving-ground wind-tunnel).

A process to create a vehicle resistance curve based on airflow predictions using Computational Fluid Dynamics (CFD) simulation technique is presented. 1-dimensional engine cooling system simulation tool KULI is used to compute the coefficients of vehicle resistance curve. A full factorial Design of Experiment (DOE) established the relationship between the coefficients and the sum of absolute difference between KULI and CFD predictions. The NLPQL optimization routine is used to accurately predict the coefficients so that sum of absolute difference between KULI and CFD predictions is minimized.

For an automotive exhaust system, noise level and back pressure are the most important parameters for passenger comfort and engine performance respectively. The sound quality perception of the existing silencer design was unacceptable, although the back pressure measured was below the target limit. To improve the existing design, few concepts were prepared by changing the internal elements of silencer only. The design constraints were the silencer shell dimensions, volume of silencer, inlet pipe and outlet tailpipe positions, which had to be kept same as that of the existing base design. The sound quality signal replaying and synthesizing was performed to define the desired sound quality. The numerical simulation involves 3D computational fluid dynamics (CFD) with appropriate boundary condition having less numerical diffusions to predict the back pressure. The various silencer concepts developed with this preliminary analysis, was then experimentally verified with the numerical data.

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.

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.

Automotive window buffeting is a source of vehicle occupant’s discomfort and annoyance. Original equipment manufacturers (OEM) are using both experimental and numerical methods to address this issue. With major advances in computational power and numerical modelling, it is now possible to model complex aero acoustic problems using numerical tools like CFD. Although the direct turbulence model LES is preferred to simulate aero-acoustic problems, it is computationally expensive for many industrial applications. Hybrid turbulence models can be used to model aero acoustic problems for industrial applications. In this paper, the numerical modelling of side window buffeting in a generic passenger car is presented. The numerical modelling is performed with the hybrid turbulence model Scale Adaptive Simulation (SAS) using a commercial CFD code.

Establishing data adjustments that will give an interference free result for bluff bodies in automotive wind tunnels has been pursued for at least the last 45 years. Recently, the Two-Measurement correction method that yields a wake distortion adjustment for open jet wind tunnels has shown promise of being able to adjust for many of the effects of non-ideal static pressure gradients on bluff automotive bodies. Utilization of this adjustment has shown that a consistent drag results when the vehicle is subjected to the various gradients generated in open jet wind tunnels. What has been lacking is whether this consistent result is independent of the other tunnel interference effects. The studies presented here are intended to fill that gap on the performance of the two-measurement technique. The subject CFD studies are designed to eliminate all wind tunnel interference effects except for the variation of the (linear) static pressure gradient.

To meet the 2010 diesel engine emission regulations, an aftertreatment system was developed to reduce HC, CO, NOx and soot. In NOx reduction, a baseline SCR module was designed to include urea injector, mixing decomposition tube and SCR catalysts. However, it was found that the baseline decomposition tube had unacceptable urea mixing performance and severe deposit issues largely because of poor hardware design. The purpose of this article is to describe necessary development work to improve the baseline system to achieve desired mixing targets. To this end, an emissions Flow Lab and computational fluid dynamics were used as the main tools to evaluate urea mixing solutions. Given the complicated urea spray transport and limited packaging space, intensive efforts were taken to develop pre-injector pipe geometry, post-injector cone geometry, single mixer design modifications, and dual mixer design options.

Using gasoline and diesel simultaneously in a dual-fuel combustion system has shown effective benefits in terms of both brake thermal efficiency and exhaust emissions. In this study, the dual-fuel approach is applied to a light-duty spark ignition (SI) gasoline direct injection (GDI) engine. Three combustion modes are proposed based on the engine load, diesel micro-pilot (DMP) combustion at high load, SI combustion at low load, and diesel assisted spark-ignition (DASI) combustion in the transition zone. Major focus is put on the DMP mode, where the diesel fuel acts as an enhancer for ignition and combustion of the mixture of gasoline, air, and recirculated exhaust gas. Computational fluid dynamics (CFD) is used to simulate the dual-fuel combustion with the final goal of supporting the comprehensive optimization of the main engine parameters.

With the advent of quieter powertrain and improved cabin acoustic sealing, there is an increased focus on noise generated in the HVAC unit and climate control ducting system. With improved insulation from exterior noise sources such as wind & road noise, HVAC noise is more perceptible by the occupants and is a key quality indicator for new generation vehicles. This has increased the use of simulations tools to predict HVAC noise during the virtual development phase of new vehicle programs. With packaging space being premium under the instrument panel, changes to address noise issues are expensive and often impractical. The current methodology includes the best practices in simulation accumulated from prior aero acoustics validation studies on fans, ducts, flaps and plenum volume discharge. The paper details the acoustic noise generation and propagation in the near field downstream of an automotive HVAC unit in conjunction with ducting system.

The objective of the work presented in this paper is to provide an overall CFD evaluation and optimization study of cabin climate control of air-conditioned (AC) city buses. Providing passengers with a comfortable experience is one of the focal point of any bus manufacturer. However, detailed evaluation through testing alone is difficult and not possible during vehicle development. With increasing travel needs and continuous focus on improving passenger experience, CFD supplemented by testing plays an important role in assessing the cabin comfort. The focus of the study is to evaluate the effect of size, shape and number of free-flow and overhead vents on flow distribution inside the cabin. Numerical simulations were carried out using a commercially available CFD code, Fluent®. Realizable k - ε RANS turbulence model was used to model turbulence. Airflow results from numerical simulation were compared with the testing results to evaluate the reliability.

Recently, the Two-Measurement correction method that yields a wake distortion adjustment for open jet wind tunnels has shown promise of being able to adjust for many of the effects of non-ideal static pressure gradients on bluff automotive bodies. Utilization of this adjustment has shown that a consistent drag results when the vehicle is subjected to the various gradients generated in open jet wind tunnels. What has been lacking is whether this consistent result is independent of the other tunnel interference effects. The studies presented here are intended to fill that gap and add more realistic model and wind tunnel conditions to the evaluations of the performance of the two-measurement technique. The subject CFD studies are designed to greatly reduce all wind tunnel interference effects except for the variation of the non-linear static pressure gradients. A zero gradient condition is generated by simulating a solid wall test section with a blockage ratio of 0.1%.

Computational tools have been extensively applied to predict component temperatures before an actual vehicle is built for testing [1, 2, 3, 4, and 5]. This approach provides an estimate of component temperatures during a specific driving condition. The predicted component temperature is compared against acceptable temperature limits. If violations of the temperature limits are predicted, corrective actions will be applied. These corrective actions may include adding heat shields to the heat source or to the receiving components. Therefore, design changes are implemented based on the simulation results. Sensitivity analysis is the formal technique of determining most influential parameters in a system that affects its performance. Uncertainty analysis is the process of evaluating the deviation of the design from its intended design target.

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.

Simulation has become an integral part in the design and development of an automotive air-conditioning (AC) system. Simulation is widely used for both system level and component level analyses and are carried out with one-dimensional (1D) and Computational Fluid Dynamics (CFD) tools. This paper describes a 1D approach to model refrigerant loop and vehicle cabin to simulate the soak and cool down analysis. Soak and cool down is one of the important tests that is carried out to test the performance of a heating, ventilation and air-conditioning (HVAC) system of a vehicle. Ability to simulate this cool down cycle is thus very useful. 1D modeling is done for the two-phase flow through the refrigerant loop and air flow across the heat exchangers and cabin with the commercial software AMESim. The model is able to predict refrigerant pressure and temperature inside the loop at different points in the cycle.

In the past few decades CNG (Compressed Natural Gas) fuel growing as an alternate fuel due to its more economically as compared to Gasoline & Diesel fuels by vehicle running cost in both passenger as well as commercial vehicles, additionally it is more environment friendly & safer fuel with respect to gasoline & diesel. At standard temperature & pressure fuel density of Natural Gas (0.7-0.9 kg/m3) is lower than Gasoline (715-780 kg/m3), Diesel (849~959 kg/m3), therefore CNG fuel require higher storage space as compared to Gasoline & Diesel & also it stores at very high pressure (200-250 bar) to further increase the fuel density 180 kg/m3 (at 200 bar) and for 215 kg/m3 (at 250 bar) in CNG cylinders so that max fuel contains in the cylinders and increase the vehicle running range per fuel filling & reduces its fuel filling frequency at filling stations.