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In recent years, customers who are looking to buy or lease a car have placed more interest in exploring electrified vehicles including Battery Electric Vehicles (BEV), Hybrid Electric Vehicles (HEV), Plug-in Hybrid Electric Vehicles (PHEV) and Fuel Cell Electric Vehicles (FCEV) as new options in the automotive market. As the recent trends suggest, this interest is likely to be solidified, and people will start buying EVs more and more. These market trends show that the internal combustion engine (ICE) drivetrain soon will be progressively replaced by the electric drive unit for passenger car applications. The electric vehicles provide positive impacts such as instant torque delivery, overall vehicle comfort, noise and vibration. They also provide local environmental benefits by reducing greenhouse gas emissions. However, there are some major complexities for EVs to overcome before completely replacing ICE vehicles.

The main purpose of this paper is to develop a reliable bench test to understand the vibratory behavior of the half shafts under applied torque comparable to an idle condition. In some cases, the half shaft path is a major factor influencing the idle vibration in the vehicle. At idle condition vehicle vibrations are caused by engine excitation and then they pass through different paths to the body structure. Half shaft manufacturers generally characterize shaft joints for their frictional behavior and typically there is no data for vibration characteristics of the half shaft under idle conditions. However, for predictive risk management, the vibratory behavior of the half shaft needs to be identified. This can be achieved from measured frequency response functions under preloaded test conditions.

An Airbus methodology for the assessment of accurate fuel pressure surge at early program stages in the complete aircraft and engine environment based on joint collaboration with LMS Engineering is presented. The aim is to comfort the prediction of the fuel pressure spike generated by an engine shutdown in order to avoid late airframe fuel system redesign and secure the aircraft entry-into-service.

The tendency for car engines to reduce the cylinder number and increase the specific torque at low rpm has led to significantly higher levels of low frequency pulsation from the exhaust tailpipe. This is a challenge for exhaust system design, and equally for body design and vehicle integration. The low frequency panel noise contributions were identified using pressure transmissibility and operational sound pressure on the exterior. For this the body was divided into patches. For all patches the pressure transmissibility across the body panels into the interior was measured as well as the sound field over the entire surface of the vehicle body. The panel contributions, the pressure distribution and transmissibility distribution information were combined with acoustic modal analysis in the cabin, providing a better understanding of the airborne transfer.

Mentor Graphics Corp. offers the only fully embedded computational fluid dynamics (CFD) solution for Solid Edge software, a mainstream computer-aided design (CAD) solution developed by Siemens’ product lifecycle management (PLM) software business.

Regulations on noise and gas emissions become more and more stringent resulting in noise abatement devices needing further engineering and optimization. Mufflers are installed at the end of powertrains to reduce the acoustic impact of the sound pressure from the engine. Such acoustic reduction is achieved through internal structures that promote destructive interference within the muffler. However, the muffler increases the backpressure downstream of the aftertreatment line, thus decreasing the engine efficiency. In the following work, an optimization workflow is presented to find the best design for a muffler geometry. The optimization is performed with the Sherpa algorithm that uses several optimization algorithms simultaneously to increase robustness and efficiency. Sherpa is implemented in an optimization tool that manages the workflow of two other software tools.

A toroidal variator is the core part of an advanced Continuously Variable Transmission (CVT) design. Knowing its behavior and internal forces is key to defining the operational conditions of the transmission. To maintain a steady-state speed ratio, or to accurately and efficiently move between speed ratios, optimal trunnion control force is required. The unique design of the toroidal CVT makes the design very sensitive to trunnion positioning and force transients. Analytical understanding of the mechanism response is critical to toroidal variator controller design. A critical feature of the toroidal CVT simulation is representation of the friction forces in the disk-roller contact. This effect is important to the mechanism torque capacity and efficiency.

Fan noise can form a significant part of the vehicle noise signature and needs hence to be optimized in view of exterior noise and operator exposure. Putting together unsteady CFD simulation with acoustic FEM modeling, tonal and broadband fan noise can be accurately predicted, accounting for the sound propagation through engine compartment and vehicle frame structure. This paper focuses on method development and validation in view of the practical vehicle design process. In a step by-step approach, the model has been validated against a dedicated test-set-up, so that good accuracy of operational fan noise prediction could be achieved. Main focus was on the acoustic transfer through the engine compartment. The equivalent acoustic transfer through radiators/heat exchangers is modeled based on separate detailed acoustic models. The updating process revealed the sensitivity of various components in the engine compartment.

The correct quantification of airborne sources and their transfer to the vehicle interior noise enables vehicle manufacturers to set system targets and to assess interior noise effects of new or modified systems. Measurements on complete vehicles and on test-beds for body, engine, exhaust, tire, HVAC etc. can then be used to estimate interior noise contributions and choose an optimal level of solutions. This study addresses exhaust tailpipe airborne noise emission in a highly controlled situation; indoors and with an exhaust simulator. Two methods of characterization are compared. One method uses the sound pressure very close to the active source as a source strength combined with pressure transmissibility to estimate the interior noise contributions. The other method uses an inverse estimate of the source volume acceleration and the pressure over volume acceleration transfer for the same purpose. The methods of airborne contribution analysis are briefly described.

This model based investigation is carried out in order to control the half order modulation for diesel engines using by virtual calibration approach and proposes a feedback control strategy to mitigate cylinder to cylinder imbalance from asymmetric cylinders torque production. Combustion heat release analysis is performed on test data to understand the root cause of observed cylinder to cylinder pressure variations. The injected fuel variations are shown to cause the observed pressure variations between cylinders. A feedback control strategy based on measured crank shaft position is devised to control the half order modulation to balance the combustion pressure profile between cylinders. This control strategy is implemented in Simulink and is tested in closed-loop with the diesel engine model in AMESim. The closed-loop performance indicates that the half order modulation is considerably improved while having minimal impact on the fuel consumption.

CFD simulations of reacting flows are fundamental investigation tools used to predict combustion behaviour and pollutants formation in modern internal combustion engines. Focusing on spark-ignited units, most of the flamelet-based combustion models adopted in current simulations use the fuel/air/residual laminar flame propagation speed as a background to predict the turbulent flame speed. This, in turn, is a fundamental requirement to model the effective burn rate. A consolidated approach in engine combustion simulations relies on the adoption of empirical correlations for laminar flame speed, which are derived from fitting of combustion experiments. However, these last are conducted at pressure and temperature ranges largely different from those encountered in engines: for this reason, correlation extrapolation at engine conditions is inevitably accepted. As a consequence, relevant differences between proposed correlations emerge even for the same fuel and conditions.

Wheel loader subsystems are multi-domain in nature, including controls, mechanisms, hydraulics, and thermal. This paper describes the process of developing a multi-domain simulation of a wheel loader. Working hydraulics, kinematics of the working tool, driveline, engine, and cooling system are modeled in LMS Imagine.Lab Amesim. Contacts between boom/bucket and bucket/ground are defined to constrain the movement of the bucket and boom. The wheel loader has four heat exchangers: charge air cooler, radiator, transmission oil cooler, and hydraulic oil cooler. Heat rejection from engine, energy losses from driveline, and hydraulic subsystem are inputs to the heat exchangers. 3D CFD modeling was done to calibrate airflows through heat exchangers in LMS Amesim. CFD modeling was done in ANSYS FLUENT® using a standard k - ε model with detailed fan and underhood geometry.

Due to the inherent computational cost of multiphysics topology optimization methods, it is a common practice to implement these methods in two-dimensions. However most real-world multiphysics problems are best optimized in three-dimensions, leading to the necessity for large-scale multiphysics topology optimization codes. To aid in the development of these codes, this paper presents a general thermomechanical topology optimization method and describes how to implement the method into a preexisting large-scale three-dimensional topology optimization code. The weak forms of the Galerkin finite element models are fully derived for mechanical, thermal, and coupled thermomechanical physics models. The objective function for the topology optimization method is defined as the weighted sum of the mechanical and thermal compliance. The corresponding sensitivity coefficients are derived using the direct differentiation method and are verified using the complex-step method.

Convolutional neural networks are the de facto method of processing camera, radar, and lidar data for use in perception in ADAS and L4 vehicles, yet their operation is a black box to many engineers. Unlike traditional rules-based approaches to coding intelligent systems, networks are trained and the internal structure created during the training process is too complex to be understood by humans, yet in operation networks are able to classify objects of interest at error rates better than rates achieved by humans viewing the same input data.

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.

This course highlights the technologies enabling ADAS and how they integrate with existing passive occupant crash protection systems, how ADAS functions perceive the world, make decisions, and either warn drivers or actively intervene in controlling the vehicle to avoid or mitigate crashes. Examples of current and future ADAS functions, and various sensors utilized in ADAS, including their operation and limitations, and sample algorithms, will be discussed and demonstrated. The course utilizes a combination of hands-on activities, including computer simulations, discussion and lecture.

Potential regulations surrounding the development, testing and commercial launch of Highly Automated Vehicles and possible liability exposure for the manufacturing and operation of Highly Automated Vehicles are fluid and changing areas, that will continue to evolve over the next several years. The first half of this course reviews where regulations are at the state and federal levels, what actions are currently under consideration, how current regulations will need to change to accommodate HAV’s, and how and when new regulations might be implemented. The second half covers both common law and strict liability and how it may apply to HAV’s.

This 4-week virtual-only experience, conducted by leading experts in the autonomous vehicle industry and academia, provides an in-depth look at the most common sensor types used in autonomous vehicle applications. By reviewing the theory, working through examples, viewing sensor data, and programming movement of a turtlebot, you will develop a solid, hands-on understanding of the common sensors and data provided by each. This course consists of asynchronous videos you will work through at your own pace throughout each week, followed by a live-online synchronous experience each Friday. The videos are led by Dr.

This 4-week virtual-only experience is conducted by leading experts in the autonomous vehicle industry and academia. You’ll develop an understanding of the fundamentals of AV architecture, including mechatronics, kinematics, and the sense-think-act framework in autonomous systems. The course builds a connection for how robotics are used in autonomous vehicles and provides you with demonstrations, procedures, and the skills necessary to program a robot with basic commands using the Robot Operating System (ROS).

The accurate representation of Internal Combustion Engine (ICE) flows via CFD is an extremely complex task: it strongly depends on a combination of highly impacting factors, such as grid resolution (both local and global), choice of the turbulence model, numeric schemes and mesh motion technique. A well-founded choice must be made in order to avoid excessive computational cost and numerical difficulties arising from the combination of fine computational grids, high-order numeric schemes and geometrical complexity typical of ICEs. The paper focuses on the comparison between different mesh motion technologies, namely layer addition and removal, morphing/remapping and overset grids. Different grid strategies for a chosen mesh motion technology are also discussed. The performance of each mesh technology and grid strategy is evaluated in terms of accuracy and computational efficiency (stability, scalability, robustness).