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Lightweight design is a key factor in general engineering design practice, however, it often conflicts with fatigue durability. This paper presents a way for improving the effectiveness of fatigue performance dominated optimization, demonstrated through a case study on suspension brackets for heavy-duty vehicles. This case study is based on random load data collected from fatigue durability tests in proving grounds, and fatigue failures of the heavy-duty vehicle suspension brackets were observed and recorded during the tests. Multi-objective fatigue optimization was introduced by employing multiaxial time-domain fatigue analysis under random loads combined with the non-dominated sorting genetic algorithm II with archives.

The phenomenon of drop-wall interaction plays a crucial role in a wide range of industrial applications. When liquid droplets come into contact with a high-temperature surface, it can lead to thermal shock due to rapid temperature fluctuations. This abrupt temperature change can generate thermal stress within the solid wall material. If the thermal stress exceeds the material's strength in that specific stress mode, it can result in material failure. Therefore, it is imperative to delve into the evolving temperature patterns on high-temperature surfaces to optimize material durability. This study focuses on investigating drop-wall interactions within the context of engine environments. To achieve this, the Smoothed Particle Hydrodynamics (SPH) method is employed to simulate the impact of fuel droplets on a silicon nitride wall. The goal is to understand the heat transfer mechanisms, thermal penetration depths, and temperature distributions within the heated wall.

Interest in electric vehicles (EVs) has significantly increased from the last decade, as the whole world is concerned about the reduction of emission of greenhouse gas by reducing the use of fossil fuel in transportation. The primary issue for electric vehicles is to develop an energy storage system i.e battery that can enable high mileage, rapid charging, and high-performance driving. Hence, battery management is required to get maximum, safe, and consistent performance of electric vehicles when running in a variety of conditions. To get the most out of a battery, it's important to keep an eye on its operating conditions, especially temperature, which has been shown to have a direct impact on battery performance and life. So, a battery thermal management system (BTMS) is crucial in the control of the thermal behavior of the battery. A good system simulation tool can minimize the time and cost of designing such a complicated thermal management system.

Understanding the fundamental details of drop/wall interactions is important to improving engine performance. Most of the drop-wall interactions studies are based on the impact of a single drop on the wall. To accurately mimic and model the real engine conditions, it is necessary to characterize spray/wall interactions with different impingement frequencies at a wide range of wall temperatures. In this study, a numerical method, based on Smoothed Particle Hydrodynamics (SPH), is used to simulate consecutive droplet impacts on a heated wall both below and above the Leidenfrost temperature. Impact regimes are identified for various impact conditions by analyzing the time evolution of the post-impingement process of n-heptane drops at different impingement frequencies and wall surface temperatures. For wall temperature below the Leidenfrost temperature, the recoiled film does not leave the surface.

With the depletion of petroleum resources around the world, the need to have fuel-efficient mobility solutions and sustainable alternative fuels for automobiles has become prominent. Hybrid Electric Vehicles (HEV) and Battery Electric Vehicles have recently gained attention in terms of fuel-efficient mobility solutions. Recent research work by the authors of these articles and many other research groups have demonstrated the suitability of ammonia as a sustainable alternative power for automobiles [1, 2, 3, 4, 5, 6, 7, 9, 18]. Ammonia has been used for a long period of time mainly as an agricultural chemical and as a sustainable and carbon-free fuel and has substantial potential as a liquid fuel for mobile applications [1, 2, 3, 4, 5, 6, 7]. Ammonia-rich fuels can be used to run HEVs equipped with an Internal Combustion Engine (ICE) as the primary power source and a battery as the secondary energy source.

A CAE-based optimization method is developed for Lube Oil Consumption (LOC) analysis of the piston-ring system. With accurate thermodynamic boundary conditions from 1D engine combustion simulation, piston motion, dynamics of piston ring, and characteristics of oil consumption are simulated using AVL Piston&Ring. The model is validated by comparing with available test data. Good match is achieved. The model is then applied to a diesel engine. The root cause of excessive LOC of the engine has been identified through CAE. The improved understanding has been applied to optimize the piston and piston ring. Engine dyno test, 1200-hour engine durability test, and 45000-kilometer vehicle test have been conducted to validate the optimized design. The experiment results are in good agreement with CAE predictions, and the oil consumption has been improved over the original design.

Experimental studies of soot particles showed that the intensity ratio of amorphous and graphite layers measured by Raman spectroscopy correlates to soot oxidation reactivities, which is very important for regeneration of the diesel particulate filters and gasoline particulate filters. This physical mechanism is absent in all soot models. In the present paper, a novel two-layer soot model was proposed that considers the amorphous and graphite layers in the soot particles. The soot model considers soot inception, soot surface growth, soot oxidation by O2 and OH, and soot coagulation. It is assumed that amorphous-type soot forms from fullerene. No soot coagulation is considered in the model between the amorphous- and graphitic-types of soot. Benzene is taken as the soot precursor, which is formed from acetylene. The model was implemented into a commercial CFD software CONVERGE using user defined functions. A diesel engine case was simulated.

Tyre behavior plays an important role in vehicle dynamics simulation. The Magic Formula Tyre Model is a semi-empirical tyre model which describes tyre behavior quite accurately in the handling simulation. The Magic Formula Tyre Model needs a set of parameters to describe the tyre properties; the determination of these parameters is nontrivial task due to its nonlinear nature and the presence of a large number of coefficients. In this paper, the homotopy algorithm is applied to the parameter identification of Magic Formula tyre model. A morphing parameter is introduced to correct the optimization process; as a result, the solution is directed converging to the global optimal solution, avoiding the local convergence. The method uses different continuation methods to globally optimize the parameters, which ensures that the prediction of the Magic Formula model can be very close to the test data at all stages of the optimization process.

Natural gas (NG) is an alternative fuel for spark-ignition engines. In addition to its cleaner combustion, recent breakthroughs in drilling technologies increased its availability and lowered its cost. NG consists of mostly methane, but it also contains heavier hydrocarbons and inert diluents, the levels of which vary substantially with geographical source, time of the year and treatments applied during production or transportation. To investigate the effects of NG composition on engine performance and emissions, a 3D CFD model of a heavy-duty diesel engine retrofitted to NG spark ignition simulated lean-combustion engine operation at low speed and medium load conditions. The work investigated three NG blends with similar lower heating value (i.e., similar energy density) but different Methane Number (MN). The results indicated that a lower MN increased flame propagation speed and thus increased in-cylinder pressure and indicated mean effective pressure.

The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

In recent years, study on the ride comfort of vehicles has attracted wide attention. The vibration caused by the road is transmitted to the human body through the tire, suspension, vehicle body, and the seat. Since the human body is in contact with the seat and the vibration is transmitted directly to the human body through the seat, the seat pan angle plays an important role on the vibration response of the human body. Previous studies have explored the effects of different backrest designs on human vibration response, but ignored the effects of different seat pan angles. Therefore, this paper will use a human biodynamic model combined with a 6-DOF seat model to study the effect of seat pan angles and feet-floor interaction on human vibration response. Three cases are proposed: Case 1 has a seat pan angle 8°, Case 2 has a seat pan angle 13°, and Case 3 has a seat pan angle 17°.

Flame speed data reported in most literature are acquired in conventional apparatus such as the spherical combustion bomb and counterflow burner, and are limited to atmospheric pressure and ambient or slightly elevated unburnt temperatures. As such, these data bear little relevance to internal combustion engines and gas turbines, which operate under typical pressures of 10-50 bar and unburnt temperature up to 900K or higher. These elevated temperatures and pressures not only modify dominant flame chemistry, but more importantly, they inevitably facilitate pre-ignition reactions and hence can change the upstream thermodynamic and chemical conditions of a regular hot flame leading to modified flame properties. This study focuses on how auto-ignition chemistry affects flame propagation, especially in the negative-temperature coefficient (NTC) regime, where dimethyl ether (DME), n-heptane and iso-octane are chosen for study as typical fuels exhibiting low temperature chemistry (LTC).

In this paper, a detailed three dimensional (3D) flexible ring tire model is first proposed which includes a rigid rim with thickness, different layers of discretized belt points and a number of massless tread blocks attached on the belt. The parameters of the proposed 3D tire model can be divided into in-plane parameters and out-of-plane parameters. In this paper, the relationship of the in-plane parameters between the 3D tire model and the 2D tire model is determined according to the connections among the tire components. Based on the determined relationship, it is shown that the 3D tire model can produce almost the same prediction results as the 2D tire model for the in-plane tire behaviors.

Vehicle tire performance is an important consideration for vehicle handling, stability, mobility, and ride comfort as well as durability. Significant efforts have been dedicated to tire modeling in the past, but there is still room to improve its accuracy. In this study, a detailed in-plane flexible ring tire model is proposed, where the tire belt is discretized, and each discrete belt segment is considered as a rigid body attached to a number of parallel tread blocks. The mass of each belt segment is accumulated at its geometric center. To test the proposed in-plane tire model, a full-vehicle model is integrated with the tire model for simulation under a special driving scenario: acceleration from rest for a few seconds, then deceleration for a few seconds on a flat-level road, and finally constant velocity on a rough road. The simulation results indicate that the tire model is able to generate tire/road contact patch forces that yield reasonable vehicle dynamic responses.

A tire may be one of the most critical and complex components in vehicle dynamics and road loads analyses because it serves as the only interface between the road surface and the vehicle. Extensive research and development activities about vehicle dynamics and tire models have been published in the past decades, but it is still not clear about the applications and parameter identification associated with all of these tire models. In this literature review study, various published tire models used for vehicle dynamics and road loads analyses are compared in terms of their modeling approaches, applications and parameters identification process and methodologies. It is hoped that the summary of this literature review work can help clarify and guide the future research and development direction about tire modeling.

In vehicle driving environment, the driver is subjected to the vibrations in horizontal, vertical, and fore-aft directions. The human body is very much sensitive to whole body vibration and this vibration transmission to the body depends upon various factors including road irregularities, vehicle suspension, vehicle dynamics, tires, seat design and the human body's properties. The seat design plays a vital role in the vibration isolation as it is directly in contact with human body. Vibration isolation properties of a seat depend upon its dynamic parameters which include spring stiffness and damping of seat suspension and cushion. In this paper, an optimization-based method is used to determine the optimal seat dynamic parameters for seat suspension, and cushion based on minimizing occupant's body fatigue (occupant body absorbed power). A 14-degree of freedom (DOF) multibody biodynamic human model in 2D is selected from literature to assess three types of seat arrangements.

This paper presents 3D finite element analysis performed for a composite cylindrical tank made of 6061-aluminum liner overwrapped with carbon fibers subjected to a burst internal pressure of 1610 bars. As the service pressure expected in these tanks is 700 bars, a factor of safety of 2.3 is kept the same for all designs. The optimal design configuration of such high pressure storage tanks includes an inner liner used as a gas permeation barrier, geometrically optimized domes, inlet/outlet valves with minimum stress concentrations, and directionally tailored exterior reinforcement for high strength and stiffness. Filament winding of pressure vessels made of fiber composite materials is the most efficient manufacturing method for such high pressure hydrogen storage tanks. The complexity of the filament winding process in the dome region is characterized by continually changing the fiber orientation angle and the local thickness of the wall.

The hydrogen economy envisioned in the future requires safe and efficient means of storing hydrogen fuel for either use on-board vehicles, delivery on mobile transportation systems or high-volume storage in stationary systems. The main emphasis of this work is placed on the high -pressure storing of gaseous hydrogen on-board vehicles. As a result of its very low density, hydrogen gas has to be stored under very high pressure, ranging from 350 to 700 bars for current systems, in order to achieve practical levels of energy density in terms of the amount of energy that can be stored in a tank of a given volume. This paper presents 3D finite element analysis performed for a composite cylindrical tank made of 6061-aluminum liner overwrapped with carbon fibers subjected to a burst internal pressure of 1610 bars. As the service pressure expected in these tanks is 700 bars, a factor of safety of 2.3 is kept the same for all designs.

Digital human modeling and posture prediction can only be used as a design tool if the predicted postures are realistic. To date, the most realistic postures have been realized by simultaneously optimizing human performance measures (HPMs). These HPMs currently consist of joint discomfort, delta potential energy, and visual displacement. However these HPMs only consider the kinematics of human posture. Dynamic aspects of human posture such as external loads and mass of limbs have not yet been considered in conjunction with the current HPMs. This paper gives the formulation for a new human performance measure combination including the use of joint torque to account for the dynamics of human posture. Postures are then predicted using multi-objective optimization (MOO) techniques to optimize the combination of the new HPM and the current. The predicted postures are then compared with the benchmark postures which are those obtained from using the current HPMs only.

Currently, the chassis assembly contributes about 73 percent of the overall weight of a 14.63 m long haul trailer. This paper presents alternative design concepts for the structural floor of a van trailer utilizing sandwich panels with various material and geometric characteristics of the core layer in order to reduce its weight significantly below that of the current design configuration. The main objective of the new designs is to achieve optimal tradeoffs between the overall structural weight and the flexural stiffness of the floor. Various preliminary design concepts of the core designs were compared on the basis of a single section of the core structure. Six different designs were analyzed by weight, maximum displacement and maximum stress under bending and torsion loads. Each concept was kept uniform by length, thickness, loading and boundary conditions. Each design concept was examined through testing of scaled model for floor assemblies.