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This paper presents a virtual analysis method for pressure spike estimation and optimization of hydraulic system architecture for off-highway applications with hydraulically actuated clutch. This pressure spike leads to a very high torque spike in driveline components during clutch pop-up conditions in puddling operations. These torque spikes lead to potential failure of driveline components i.e., gear, shaft, bearing and torsional damper during sudden engagement events. To assess the hydraulic system performance during clutch pop-up cornering conditions is very challenging and leads to compromise on operator safety in the paddy field. It is essential to develop a simulation methodology in a virtual environment to understand the system behavior during clutch pop-up condition and impact of various hydraulic system parameters. This paper describes a Model Based System Design (MBSD) approach for understanding hydraulic system pressure spike phenomenon and dynamic response.

A typical cab used on agriculture machines is made up of a metal frame structure with large enclosing panels of glass, plastic, and metal. Acoustic treatments such as coatings, textiles and foams are used within the cab for aesthetics but also to mediate undesired noise. To develop effective designs for the cab to combat noise, accurate tools for measurement, and predictive methods for sound transmission loss are needed. This paper focuses on Sound Transmission Loss (STL) of the rear upper panel of a cab used in agriculture machines. Results from CAE based tools such as Statistical Energy Analysis (SEA), Finite Element Analysis (FEA) and Hybrid FE-SEA methods are compared to measurements. The panel studied included features such as curvature, deep drawn beads with a glass window and a damping coating. The simulation results are refined by incorporating methods for accurate modeling of ribs stiffness, curvature effect and radiation efficiency by synthetic modal approach.

RADAR Sensors are going to be an integral part of autonomous vehicles. One of the main objectives of these sensors in autonomous vehicles is to get the Doppler range profile for surrounding traffic. In this paper, we use a similar RADAR for ground speed sensing in the off-highway scenario. There are several challenges in integrating the RADAR sensor with vehicles such as sensor position from ground, location on vehicle, electromagnetic interference with other electronic devices, enclosure design etc. Ground conditions and properties are also critical in the off-highway scenario for speed sensing. We propose to use the physics based electromagnetic field solvers to understand and mitigate some of these challenges and speed up the design. Electromagnetic field solvers tend to scale poorly with distance of propagation, especially in 3D modeling.

The presence of residual stresses affects the fatigue response of welded components. In the present study of thick welded cantilever specimens, residual stresses were measured in two A36 steel samples, one in the as-welded condition, and one subjected to a short history of bending loads where substantial local plasticity is expected at the fatigue hot-spot weld toe. Extensive X-Ray Diffraction (XRD) measurements describe the residual stress state in a large region above the weld toe both in an untested as-welded sample and in a sample subjected to a short load history that generated an estimated 0.01 strain amplitude at the stress concentration zone at the weld toe. The results show that such a test will significantly alter the welding-induced residual stresses. Fatigue life prediction methods need to be aware that such alterations are possible and incorporate the effects of such cyclic stress relaxation in life computations.

Pass-by/exterior noise of earth moving machines (EMM) and forestry machines is becoming a focus at early product development stages. ISO 6395 (2) or EC/2000/14 (1) standards defines exterior noise test procedure for EMM. However, these standards do not provide insights for diagnosing any noise issues which may arise. The analysis challenges are posed by the moving machine and acoustic sources with respect to the stationary hemisphere target microphone on the ground and changing operating condition of sources as function of time. There is need to develop a seamless methodology to identify acoustic sources, quantify respective source strengths and rank partial contributions from each source to the total target microphone response in order to overcome the aforementioned challenges.

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 demands on improving the noise, vibration and harshness of the golf mowing machines are growing rapidly. Low frequency vibrations at the human touchpoints are one of the important factors leading to the discomfort of operators on these machines. In the present work, low frequency vibrations experienced by the operator of the golf mowing machine are reduced using finite element analysis (FEA) and validated by a physical test. Initially, testing observed high vibration at the command arm, where some of the operating controls are placed. FEA was carried out on a frame level assembly and the design was iterated to affect these vibration levels. The golf mowing machine considered in this work is powered by a gasoline engine, which is the source of excitation in the current scenario. The operational forces of the engine were measured by using blocked-force transfer path analysis at its mounts. The modal frequency response analysis used these calculated forces as an input excitation.

This paper details results of a numerical and experimental investigation into the relative performance of vaned and vaneless mixed flow turbines for application to medium and heavy-duty diesel engines utilizing pulse exhaust systems. Previous investigations into the impact of nozzle vanes on turbine performance considered only open turbine housings, whereas a majority of medium and heavy-duty diesel engine applications are six-cylinder engines using pulse exhaust systems with divided turbines. The two turbine stages for this investigation were carefully designed to meet the constraints of engines with pulse exhaust systems and to control confounding factors that would undermine the vaned vs vaneless performance comparison. Detailed CFD analysis and turbine dynamometer test results confirm a significant efficiency advantage for the vaned turbine stage under both full and partial admission conditions.

In any machinery, avoiding noise and vibration completely is a difficult task due to the structural dynamic behaviors of components. To safeguard the operator, it is important to best isolate the operator station from NVH environment. Cabin isolation is an important aspect to minimize structure borne noise and tactile vibrations to be transferred into the cabin. Isolators are selected based on the isolation system inertial properties at mounting locations in the operating frequency range interested. The most important assumption to select isolators are that the active side and passive side of the isolators are nearly rigid so impedance mismatch is created for effective isolation. This paper describes the importance of dynamic stiffness of the structures on both the active and passive side for better NVH performance.

Operator noise is an important aspect for noise and vibration of off-highway vehicles and a quieter cab is critical for the operator comfort. The noise level inside the cab is influenced by structural and acoustic transfer paths. In this paper, we used hybrid FE-SEA approach to consider both structural and acoustic transfer path as FEM and SEA methods individually face limitations in high and low frequencies respectively. A hybrid FE-SEA cab model was built to predict the structural and acoustic transfer functions. The analysis model was built with the systematic approach validated at each step with the laboratory test results. For the structural transfer function, structural excitations were applied at four cab mount locations and accelerations at various locations on the cab were validated. For the acoustic transfer function, the cab was excited with the volume velocity source inside the cab and sound power output of various panels were calculated and compared to the test results.

The Society of Automotive Engineers Fatigue Design & Evaluation Committee [SAE FD&E] is actively working on a total life project for weldments, in which the welding residual stress is a key contributor to an accurate assessment of fatigue life. Physics-based welding process simulation and various types of residual stress measurements were pursued to provide a representation of the residual stress field at the failure location in the fatigue samples. A well-controlled and documented robotic welding process was used for all sample fabrications to provide accurate inputs for the welding simulations. One destructive (contour method) residual stress measurement and several non-destructive residual stress measurements-surface X-ray diffraction (XRD), energy dispersive X-ray diffraction (EDXRD), and neutron diffraction (ND)-were performed on the same or similarly welded samples.

The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.

Diesel engine downsizing aimed at reducing fuel consumption while meeting stringent exhaust emissions regulations is currently in high demand. The boost system architecture plays an essential role in providing adequate air flow rate for diesel fuel combustion while avoiding impaired transient response of the downsized engine. Electric Turbocharger Assist (ETA) technology integrates an electric motor/generator with the turbocharger to provide electrical power to assist compressor work or to electrically recover excess turbine power. Additionally, a variable geometry turbine (VGT) is able to bring an extra degree of freedom for the boost system optimization. The electrically-assisted turbocharger, coupled with VGT, provides an illuminating opportunity to increase the diesel engine power density and enhance the downsized engine transient response. This paper assesses the potential benefits of the electrically-assisted turbocharger with VGT to enable heavy-duty diesel engine downsizing.

Today’s business climate and economy demand new, innovative strategies from the initial kickoff of research and development - to the mining of ore from the earth - to the final inspection of a finished product in a mid-western factory. From startup companies with two employees to the largest companies, the world faces new and challenging requirements every day. The demands from companies, customers, executives, and shareholders continue to drive for higher outputs with more efficient use of personnel and investments. Fortunately, the rate of technology continues to exponentially accelerate, which allows those at the cutting edge of technology to capitalize. Caterpillar has been a pioneer in advanced technology since its inception and has been developing the foundation for autonomy over the past four decades.

A transformation of agriculture reached commercial reality at the beginning of this century as automated steering of agricultural machine systems increased the productivity and convenience in crop production systems. Following guidance, additional technologies have resulted in increasing optimized machine productivity. Today, integrated worksite solutions through machine and information management continues to transform agriculture. This is the precursor to autonomous worksite solutions that lead to the optimization of the worksite ecosystem. This paper will review the progress from the perspective of the customer value provided by increasing automated systems and the industry execution of autonomous driving technologies and will enable the pathways to autonomous worksites.

China has become the world’s largest vehicle market in terms of sales volume. Automobiles sales keep growing in recent years despite the declining economic growth rate. Due to the increasing attention given to the environmental impact, more stringent emission regulations are being drafted to control traditional internal combustion engine emissions. In order to reduce vehicle emissions, environmentally-friendly new-energy vehicles, such as electric vehicles and plug-in hybrid vehicles, are being promoted by government policies. The Chinese government plans to boost sales of new-energy cars to account for about five percent of China’s total vehicle sales. It is well known that more electric and electronic components will be integrated into a vehicle platform during vehicle electrification.

In this paper, residual stress distributions in rectangular bars due to rolling or burnishing at very high rolling or burnishing loads are investigated by roll burnishing experiments and three-dimensional finite element analyses using ABAQUS. First, roll burnishing experiments on rectangular bars at two roller burnishing loads are presented. The results indicate the higher burnishing load induces lower residual stresses and the higher burnishing load does not improve fatigue lives. Next, in the corresponding finite element analyses, the roller is modeled as rigid and the roller rolls on the flat surface of the bar with a low coefficient of friction. The bar material is modeled as an elastic-plastic strain hardening material with a nonlinear kinematic hardening rule for loading and unloading.

Engine electrification is a critical technology in the promotion of engine fuel efficiency, among which the electrified turbocharger is regarded as the promising solution in engine downsizing. By installing electrical devices on the turbocharger, the excess energy can be captured, stored, and re-used. The electrified turbocharger consists of a variable geometry turbocharger (VGT) and an electric motor (EM) within the turbocharger bearing housing, where the EM is capable in bi-directional power transfer. The VGT, EM, and exhaust gas recirculation (EGR) valve all impact the dynamics of air path. In this paper, the dynamics in an electrified turbocharged diesel engine (ETDE), especially the couplings between different loops in the air path is analyzed. Furthermore, an explicit principle in selecting control variables is proposed. Based on the analysis, a model-based multi-input multi-output (MIMO) decoupling controller is designed to regulate the air path dynamics.

All around the world, steps are being taken to improve the quality of our environment. Prominent among these are the definition, implementation, and attainment of increasingly stringent emissions regulations for all types of engines, including off-highway diesels. These rigorous regulations have driven use of technologies like after-treatment, advanced air systems, and advanced fuel systems. Fuel dispensed off-highway is routinely and significantly dirtier than fuel from on-highway outlets. Furthermore, fuels used in developing countries can be up to 30 times dirtier than the average fuels in North America. Poor fuel cleanliness, coupled with the higher pressures and performance demands of modern fuel systems, create life challenges greater than encountered with cleaner fuels. This can result in costly disruption of operations, loss of productivity, and customer dissatisfaction in the off-highway market.

The application of Artificial Intelligence (AI) in the automotive industry can dramatically reshape the industry. In past decades, many Original Equipment Manufacturers (OEMs) applied neural network and pattern recognition technologies to powertrain calibration, emission prediction and virtual sensor development. The AI application is mostly focused on reducing product development and validation cost. AI technologies in these applications demonstrate certain cost-saving benefits, but are far from disruptive. A disruptive impact can be realized when AI applications finally bring cost-saving benefits directly to end users (e.g., automation of a vehicle or machine operation could dramatically improve the efficiency). However, there is still a gap between current technologies and those that can fully give a vehicle or machine intelligence, including reasoning, knowledge, planning and self-learning.