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Road vibrations cause fatigue failures in vehicle components and systems. Therefore, reliable and accurate damage and life assessment is crucial to the durability and reliability performances of vehicles, especially at early design stages. However, durability and reliability assessment is difficult not only because of the unknown underlying damage mechanisms, such as crack initiation and crack growth, but also due to the large uncertainties introduced by many factors during operation. How to effectively and accurately assess the damage status and quantitatively measure the uncertainties in a damage evolution process is an important but still unsolved task in engineering probabilistic analysis. In this paper, a new procedure is developed to assess the durability and reliability performance, and characterize the uncertainties of damage evolution of components under constant amplitude loadings.

This paper focuses on the manufacturer's conflict in the conceptual design of commercial vehicles between highly customized special vehicles and the greatest possible degree of standardization. Modularity and standardization are crucial success factors for realizing high variance at the best cost efficiency in development and production as well for achieving the highest quality standards at reduced efforts for technical validation. The presented virtual design approach for commercial vehicle concepts allows for purposeful design and integration of new concepts and technologies on the component level in an existing product portfolio - not neglecting manufacture's portfolio requirements concerning standardization and modularity. The integrated tool chain helps to bring trade-offs to a head that exist in balancing between dedicated vehicles with best customer-relevant characteristics and standardized vehicles with the highest degree of commonality.

The ride comfort of the commercial vehicle is mainly affected by several vibration isolation systems such as the primary suspension system, engine mounting system and the cab mounting system. A rigid-flexible coupling model for the truck was built and analyzed in multi-body environment (ADAMS). The method applying the excitation on the wheels center and the engine mountings in time domain was presented. The variables' effects on the ride performance were studied by design of experiment (DOE). The optimal design was obtained by the co-simulation of the ADAMS/View, iSIGHT and Matlab. It was found that the vertical root mean square (RMS) acceleration and frequency-weighted RMS acceleration on the seat track were reduced about 17% and 11% respectively at different speeds relative to baseline according to ISO 2631-1.

Researches for automated construction machinery have been conducted for labor-saving, improved work efficiency and worker's safety, where a tracking control function was proposed as one of the key control system strategies for highly automated productive hydraulic excavators. An optimized digging trajectory that assures as much soils scooped as possible and less energy consumption is critical for an automated hydraulic excavator to improve work efficiency. Simulation models that we used to seek an optimized digging trajectory in this study consist of soil models and front linkage models of a hydraulic excavator. We developed two types of soil models. One is called wedge models used to calculate reaction forces from soils acting on a bucket during digging operation, based on the earth pressure theory. The other is called Distinct Element Method (DEM) model used to analyze soil behaviors and estimate amounts of soils scooped and reaction forces quantitatively.

This paper describes a method for optimization of engine settings in view of best total cost of operation fluids. Under specific legal NOX tailpipe emissions requirements the engine out NOX can be matched to the current achievable SCR NOX conversion efficiency. In view of a heavy duty long haul truck application various specific engine operation modes are defined. A heavy duty diesel engine was calibrated for all operation modes in an engine test cell. The characteristics of engine operation are demonstrated in different transient test cycles. Optimum engine operation mode (EOM) selection strategies between individual engine operation modes are discussed in view of legal test cycles and real world driving cycles which have been derived from on-road tests.

Shift quality of a manual transmission is a critical characteristic that requires utmost care while structuring the transmission. Shift quality is affected by many factors viz. synchronizer design, shifter design, gear design, transmission oil selection etc. This paper presents a correlation between stiffness of the shift fork in manual transmission with the gear shift quality using a gear shift quality assessment setup. Stiffness of shifter fork is optimized using contact pattern analysis and stiffness analysis on MSC Nastran. All the subsystem (i.e. synchronizer and the shift system component) are constrained to optimize the shift fork stiffness. A-5-speed manual transmission is used as an example to illustrate the same. A direct correlation of gear shift fork stiffness with the shift force experienced by the driver is established. The shift system was modeled in the UG NX 6.0 software to collate the synchronization force, shift system gap etc with the constraint on the shift fork.

In this paper, the performance simulation model of a domestic self-dumping truck was established using AVL-Cruise software. Then its accuracy was checked by the power performance and fuel economy tests which were conducted on the proving ground. The power performance of the self-dumping truck was evaluated through standing start acceleration time from 0 to 70km/h, overtaking acceleration time from 60 to 70km/h, maximum speed and maximum gradeability, while the composite fuel consumption per hundred kilometers was taken as an evaluation index of fuel economy. A L9 orthogonal array was applied to investigate the effect of three matching factors including engine, transmission and final drive, which were considered at three levels, on the power performance and fuel economy of the self-dumping truck. Furthermore, the grey relational grade was proposed to assess the multiple performance responses according to the grey relational analysis.

Rear underrun protection device is crucial for rear impact and rear under-running of the passenger vehicles to the heavy duty trucks. Rear underrun protection device design should obey the safety regulative rules and successfully pass several test conditions. The objective and scope of this paper is the constrained optimization of the design of a rear underrun protection device (RUPD) beam of heavy duty trucks for impact loading using correlated CAE and test methodologies. In order to minimize the design iteration phase of the heavy duty truck RUPD, an effective, real-life testing correlated, finite element model have been constructed via RADIOSS software. Later on, Pareto Optimization has been applied to the finite element model, by constructing designed experiments. The best solution has been selected in terms of cost, manufacturing and performance. Finally, real-life verification testing has been applied for the correlation of the optimum solution.

In tire development, the dynamic tire-road contact forces are an important indicator to assess structure-borne interior cabin noise. This type of noise is the dominant source in the frequency range from 50-450 Hz, especially when rolling with constant angular velocity on a rough road. The spatial force distribution is difficult or sometimes even impossible to simulate or measure in practice. So, the use of an inverse technique is proposed. This technique uses response measurements in combination with a digital twin simulation model to obtain the input forces in an inverse way. The responses and model properties are expressed in the time domain, since it is specifically aimed to trace back the impact locations from road surface texture indents on the tire. In order to do so, the transient responses of the travelling waves as a result of these impacts is used. The framework expresses responses as a convolution product of the unknown loads and impulse response measurements.

To improve overall customer experience, it is imperative to minimize the noise levels inside agricultural equipment cab. Up-front prediction of acoustic performance in product development is critical to implement the noise control strategies optimally. This paper discusses the methodology used for virtual modeling of a cab on agricultural equipment for prediction of interior noise. The Statistical Energy Analysis (SEA) approach is suitable to predict high frequency interior noise and sound quality parameters such as articulation index and loudness. The cab SEA model is developed using a commercial software. The structural and acoustic excitations are measured through physical testing in various operating conditions. The interior noise levels predicted by the virtual model are compared with the operator ear noise levels measured in the test unit. The resultant SPL spectrum from SEA correlates well with the test.

The lightweight design of a vehicle can save manufacturing costs and reduce greenhouse gas emissions. For the off-road vehicle and truck, the chassis frame is the most important load-bearing assembly of the separate frame construction vehicle. The frame is one of the most assemblies with great potential to be lightweight optimized. However, most of the vehicle components are mounted on the frame, such as the engine, transmission, suspension, steering system, radiator, and vehicle body. Therefore, boundaries and constraints should be taken into consideration during the optimal process. The finite element (FE) model is widely used to simulate and assess the frame performance. The performance of the frame is determined by the design parameters. As one of the largest components of the vehicle, it has a lot of parameters. To improve the optimum efficiency, sensitivity analysis is used to narrow the range of the variables.

Due to recent infrastructural development and emerging competitive automotive markets, there is seen a huge shift in customer’s demand and vehicle drivability pattern in commercial vehicle industry. Now apart from ensuring better vehicle durability and best in class tyre life and fuel mileage, a vehicle manufacturer also has to focus on other key attributes like driver’s safety and ride comfort. Thus, for ensuring enhanced drivability, key parameters for ensuring better vehicle handling includes optimization of bump steer and brake steer. Both bump steer and brake steer are vehicle’s undesirable phenomenon where a driver is forced to constantly make steering wheel correction in order to safely maneuver the vehicle in the desired path.

CNG has proven to be a concrete alternative to gasoline and diesel fuel for sustained mobility. Due to stringent emission norms and sanctions being imposed on diesel fuel vehicles, OEMs have shifted their attention towards natural gas as an efficient and green fuel. Newly implemented BS VI emission norms in India have stressed on the reduction of Nitrogen Oxides (NOx) from the exhaust by almost 85% as compared to BS IV emission norms. Also, Indian Automotive market is fuel economy cautious. This challenges to focus on improving fuel economy but without increase in NOx emissions. Exhaust Gas Recirculation (EGR) has the potential to reduce the NOx emissions by decreasing the in-cylinder temperature. The objective of the paper is to model a CNG TCIC engine using 1D simulation in order to optimize the NOx emissions and maintain exhaust temperatures under failsafe limits.

Electric vehicles have a limitation of limited range and long charging time. Energy optimization plays a very crucial role in determining the range of an electric vehicle. The innovative system proposed here gives the opportunity to reduce energy wastage and efficiently direct the electrical energy to improve the driving range of a 9 meter AC electric bus. The high voltage air conditioner unit alone consumes more than 40% of the electrical energy stored in the traction battery which reduces the driving range of the electric bus drastically. The proposed system optimizes the air conditioner utilization to direct cool air only in areas where passengers are present. Buses do not always run on full capacity, when there are less number of people in the bus the system detects the locations of the passengers using sensors and occupant detection algorithm, this enables the controller to identify the areas where cooling has to be focused and where cooling can be reduced or stopped.

A computational fluid dynamics (CFD) guided design optimization was conducted for the piston bowl geometry for a heavy-duty diesel engine. The optimization goal was to minimize engine-out NOx emissions without sacrificing engine peak power and thermal efficiency. The CFD model was validated with experiments and the combustion system optimization was conducted under three selected operating conditions representing low speed, maximum torque, and rated power. A hundred piston bowl shapes were generated, of which 32 shapes with 3 spray angles for each shape were numerically analyzed and one optimized design of piston bowl geometry with spray angle was selected. On average, the optimized combustion system decreased nitrogen oxide (NOx) emissions by 17% and soot emissions by 41% without compromising maximum engine power and fuel economy.

As the FTP-75 drive cycle does not have a prescribed gear shift pattern, automotive OEMs have the flexibility to design. Conventionally, gear shift pattern was formulated based on trial and error method, typically with 10 to 12 iterations on chassis dynamometer. It was a time consuming (i.e. ~ 3 to 4 months) and expensive process. This approach led to declaring poor fuel economy (FE). A simulation procedure was required to generate a gear shift pattern that gives optimal trade-off amongst conflicting objectives (FE, performance and emissions). As a result, a simulation tool was developed in MATLAB to generate an optimum gear shift pattern. Three different SUV/UV models were used as test vehicles in this study. Chassis dyno testing was conducted, and data was collected using the base and optimized gear shift patterns. Dyno test results with optimized gear shift pattern showed FE improvement of ~ 4 to 5% while retaining the NOx margin well above engineering targets.

With the continuous development of various technologies in the field of electric vehicles, more and more mature products are put into the market. Among them, electric commercial vehicle has been supported by many preferential policies because of its wide use and high energy utilization and has developed rapidly in recent years. At present, the electric drive-train systems of commercial vehicles can be divided into motor direct drive, integrated el-axle and distributed e-wheel drive. The first type only uses motor to replace the engine, and the other parts have little change. This method has low transmission efficiency and loose structure, which is a temporary transition scheme. The drive types of integrated E-axle and distributed E-wheel have their own advantages and disadvantages, which way to become the mainstream of the future have not yet been decided.

Increasing demands for high fuel efficiency requires imperative light weighting of automotive structure, but this adversely affects the NVH performance since transfer path of noise sources like engine, road, wind to vehicle interior through the panels weakens. Also increasing customer centric approach drives the urge to provide world-class comfort which is cost-effective too. Sound Packaging helps us to optimize this transfer paths through the panel, and can effectively complement efforts of testing team, by reducing the redundant iterations required to conclude to most effective trims to be put on. statistical energy analysis based simulations is employed for carrying out these iterations at the virtual validation gateway itself.

Adjuster rings are used in commercial vehicle axle assembly to preload differential bearings and provide support in the axial direction. Adjuster along with the carrier and bearing cap combined to form a threaded joint. Adjuster with external threads engages with internal threads formed in carrier and bearing cap. Preload in differential assembly maintains the system rigidity and helps to maintain an optimized hypoid gear engagement. An adequate preload is important to achieve a desirable bearing life. Reduction in thread engagement at adjuster joint fully or partially will cause a reduction in preload and can lead to gear misalignment. This can cause severe durability concerns. In some cases, it is observed that under vehicle operating loads adjuster ring is backed off from its assembled condition by bending the split pin (split pin is, positive lock, used to maintain adjuster position) and adjuster threads were stripped off.

Fuel efficiency is critical aspect for commercial vehicles as fuel is major part of operational costs. To complicate scenario further, fuel efficiency testing, unlike in passenger cars is more time consuming and laborious. Thus, to save on development cost and save time in actual testing, simulations plays crucial role. Typically, actual vehicle speed and gear usage is captured using reference vehicle in desired route and used it for simulation of target vehicle. Limitation to this approach is captured duty cycle is specific to powertrain and driver behavior of reference vehicle. Any change in powertrain or vehicle resistance or driver of target vehicle will alter duty cycle and hence duty cycle of reference vehicle is no more valid for simulation assessment. This paper demonstrates approach which uses combination of tools to address this challenge. Simulation approach proposed here have three parts.