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A variety of structures resonate when they are excited by external forces at, or near, their natural frequencies. This can lead to high deformation which may cause damage to the integrity of the structure. There have been many applications of external devices to dampen the effects of this excitation, such as tuned mass dampers or both semi-active and active dampers, which have been implemented in buildings, bridges, and other large structures. One of the active cancellation methods uses centrifugal forces generated by the rotation of an unbalanced mass. These forces help to counter the external excitation force coming into the structure. This research focuses on active force cancellation using centrifugal forces (CFG) due to mass imbalance and provides a virtual solution to simulate and predict the forces required to cancel external excitation to an automotive structure. This research tries to address the challenges to miniaturize the CFG model for a body-on-frame truck.

This paper delves into the investigation of flatness-based active damping control for hybrid vehicle transmissions. The main objective is to improve the current in-production controller performances without the need for additional sensors or observers. The primary goals include improving torque setpoint tracking, enhancing robustness margins, and ensuring zero steady-state torque correction. The investigation proceeds in several steps: Initially, both the general differential flatness property and the identification of flat outputs in linear dynamical systems are revisited. Subsequently, the bond graph formalism is employed to deduce straightforwardly the dynamical equations of the system. Next, a new flat output of the vehicle transmission is identified and utilized to formulate the trajectory tracking controller to align with the required control objectives and to fulfill the system constraints.

Through real-time online optimization, the full potential of the performance and energy efficiency of multi-gear, multi-mode, series–parallel hybrid powertrains can be realized. The framework allows for the powertrain to be in its most efficient configuration amidst the constantly changing hardware constraints and performance objectives. Typically, the different gears and hybrid/electric modes are defined as discrete states, and for a given vehicle speed and driver power demand, a formulation of optimization costs, usually in terms of power, are assigned to each discrete states and the state which has the lowest cost is naturally selected as the desired of optimum state. However, the optimization results would be sensitive to numerical exactitude and would typically lead to a very noisy raw optimum state. The generic approach to stabilization includes adding hysteresis costs to state-transitions and time-debouncing.

With the proliferation of electric vehicles in the market, it has become important for Automotive OEMs (Original Equipment Manufacturers) to focus on delivering a higher driving range while also maximizing performance. One approach OEMs are actively considering in meeting this goal is to include a secondary drive axle disconnect into the powertrain which has the potential to improve the overall driving range by about 6-8.3% [4]. This paper outlines the need for a novel controls architecture to make the Powertrain controls software modular and to reduce the development time needed to provide robust powertrain control software. To do this, the electrified powertrain torque controls at STELLANTIS NV takes a decentralized controls architecture approach, by separating the axle disconnect controls subsystem (ADCS) from the primary path of torque controls. The ADCS takes in information such as the desired axle state and controls the axle disconnect actuators to achieve that state.

During input tracking, closed-loop performance is strongly influenced by the dynamic of the system under control. Internal and external delays, such as actuation and measurement delays, have a detrimental effect on the bandwidth and stability. Additionally, production controllers are discrete in nature and the sampling time selection is another critical factor to be considered. In this paper we analyze the impact of both transported delay and controller sampling time on tracking performance using an electric machine speed-control problem as an example. A simple linear PI controller is used for this exercise. Furthermore, we show how the PI parameters can be adjusted to maintain a certain level of performance as the delays and sampling times are modified. This is achieved through an optimization algorithm that minimizes a specifically designed cost function.

One of the building blocks of the Stellantis hybrid powertrain embedded control software computes the maximum and minimum values of objective functions, such as output torque, as a function of engine torque, hybrid motor torque and other variables. To test such embedded software, an offline reference function was created. The reference function calculates the ideal minimum and maximum values to be compared with the output of the embedded software. This article presents the offline reference function with an emphasis on mathematical novelties. The reference function computes the minimum and maximum points of a linear objective function as a function of six independent variables, subject to 42 linear and two nonlinear constraints. Concave domains, curved surfaces, disjoint domains and multiple local extremum points challenge the algorithm. As a theorem, the conditions and methods for running trigonometric calculations in 6D Euclidean space are presented.

The Brake judder is a low-level vibration caused due to Disc Thickness Variation (DTV), Temperature, Brake Torque Variation (BTV), thermal degradation, hotspot etc. which is a major concern for the past decades in automobile manufacturers. To predict the judder performance, the modelling methods are proposed in terms of frequency and BTV respectively. In this study, a mathematical model is constructed by considering full brake assembly, tie rod, coupling rod, steering column, and steering wheel as a spring mass system for identifying judder frequency. Simulation is also performed to predict the occurrence of brake judder and those results are validated with theoretical results. Similarly, for calculating BTV a separate methodology is proposed in CAE and validated with experimental and theoretical results.

In a passenger car, suspension link bushings, engine and transmission mount bushings and bump-stops are made of elastomeric materials, to maximize the durability and comfort. Thus, deformation behavior of rubber and its durability is important for product design and development. In virtual engineering, simulating rubber fatigue is a complex exercise, since it needs right modeling strategy and coupon based testing material data. Principal stretches based Ogden model is used to characterize the hyper elastic deformation behavior of natural rubber. Fatigue crack growth approach used here for the fatigue analysis. Engine torque strut mount is used to control the engine and transmission fore aft motion and it is connected between body and Powertrain (PT) system. Powertrain events are predominant for damage contribution to mount failure. So, it is important to predict fatigue life of mount elastomer bushing under Powertrain loading.

In the light duty diesel segment, the need persists for an advanced control system to monitor the health of an aftertreatment system throughout a vehicle’s life in order to maintain compliance with ever tightening emissions levels. In on-board diagnostics (OBD), every diagnostic is validated during development stages to detect when a system under monitoring of that diagnostic has failed. This necessitates the need to create parts which represent a failure that would be observed on the vehicle. These failed parts, referred to as limit or threshold parts, are developed through a limit part creation process. Although there are commonalities amongst Original Equipment Manufacturers (OEM), each OEM has their own detection logic which will require a unique and specific limit part. Various methods exist for creating these limit parts, and each method produces a different combination of ability to detect the failure and its associated tailpipe emissions.

Most of the applications of magnesium in lightweighting commercial cars and trucks are die castings rather than sheet metal, and automotive applications of magnesium sheet have typically been experimental or low-volume serial production. The overarching objective of this collaborative research project organized by the United States Automotive Materials Partnership (USAMP) was to develop new low-cost magnesium alloys, and demonstrate warm-stamping of magnesium sheet inner and outer door panels for a 2013 MY Ford Fusion at a fully accounted integrated component cost increase over conventional steel stamped components of no more than $2.50/lb. saved ($5.50/kg saved). The project demonstrated the computational design of new magnesium (Mg) alloys from atomistic levels, cast new experimental alloy ingots and explored thermomechanical rolling processes to produce thin Mg sheet of desired textures.

Strength and fatigue assessment of chassis components are essentially influenced by the material used and manufacturing processes chosen. The manufacturing process of chassis components decides the variation in the mechanical properties of the component, which has an impact on the strength/fatigue performance. Investigating the design concerning the manufacturing processes is vital to the industry. Standard computer aided engineering (CAE) procedures for validating the alloy wheels usually consider the material properties as homogeneous. There was a gap between test results and CAE durability prediction (as per standard procedure). Incorporating the manufacturing process related characteristics with the strength simulation will be a viable solution to reduce this gap. This study was intended at developing a procedure for the strength analysis of an alloy wheel by considering the manufacturing process.

In this study we collect and analyze data on how hands-free automated lane centering systems affect the controllability of a hazardous event during an operational situation by a human operator. Through these data and their analysis, we seek to answer the following questions: Is Level 2 and Level 3 automated driving inherently uncontrollable as a result of a steering failure? Or, is there some level of operator control of hazardous situations occurring during Level 2 and Level 3 automated driving that can reasonably be expected, given that these systems still rely on a driver as the primary fall back. The controllability focus group experiments were carried out using an instrumented MY15 Jeep® Cherokee with a prototype Level 2 automated driving system that was modified to simulate a hands-free steering system on a closed track with speeds up to 110kph. The vehicle was also fitted with supplemental safety measures to ensure experimenter control.

The Press-in-Place (PIP) gasket is a static face seal with self-retaining feature, which is used for the mating surfaces of engine components to maintain the reliability of the closed system under various operating conditions. Its design allows it to provide enough contact pressure to seal the internal fluid as well as prevent mechanical failures. Insufficient sealing pressure will lead to fluid leakage, consequently resulting in engine failures. A test fixture was designed to simulate the clamp load and internal pressure condition on a gasket bolted joint. A sensor pad in combination with TEKSCAN equipment was used to capture the overall and local pressure distribution of the PIP gasket under various engine loading conditions. Then, the test results were compared with simulated results from computer models. Through the comparisons, it was found that gasket sealing pressure of test data and CAE data shows good correlations in all internal pressure cases when the bolt load was 500 N.

For the designing of world class vehicles, ride comfort is one of the criteria that vehicle manufacturers are constantly trying to improve. The automotive seating system is an important sub-system in a vehicle that contributes to the ride comfort of the vehicle occupants. Seat vibrations are perceived by the occupants and make them feel uncomfortable during driving conditions. These vibrations are majorly transferred from engine and road excitation loads. For road excitation loads, the road testing may not be accurately repeatable, and measurements based on four post shakers are used to assess the discomfort. The major challenges for the vehicle manufactures is the availability of physical prototypes at an early stage of vehicle development and any changes in the design due to test validation leads to huge cost and time.

The reduction of automotive emissions is instrumental in the fight against air pollution and its impact on global warming. This realization has empowered governments around the world to mandate lower levels of vehicle emissions requiring the Original Equipment Manufacturers (OEMs) to implement advanced aftertreatment technologies in their applications. Achieving emission levels as low as SULEV30 or SULEV20 would have been impossible only a couple of decades ago, however, these lower levels of emissions are now a possibility through advanced control strategies and aftertreatment systems. As a part of this mandate to lower emissions, OEMs are also continuously monitoring the health and performance of their aftertreatment and control components. The implementation of On Board Diagnostics (OBD) ensures that control systems are functioning robustly and the emission levels are achieved and maintained to high mileages for the life of the vehicle.

Rapid Compression Machines (RCM) offer the ability to easily change the compression ratio and the pressure/mixture composition/temperature to gather ignition delay data at various engine relevant conditions. Therefore, RCMs with optical access to the combustion chamber can provide an effective way to analyze macroscopic spray characteristics needed to understand the spray injection process and for spray model development, validation and calibration at conditions that are suitable for engines. Fuel surrogates can help control fuel parameters, develop models for spray and combustion, and perform laser diagnostics with known fluorescence characteristics. This study quantifies and evaluates the macroscopic spray characteristics of multicomponent gasoline surrogates in comparison to their gasoline counterparts, under gasoline direct injection (GDI) engine conditions.

With the demand of growing cooling requirements of fast charging and new thermal architecture design in battery electric vehicles, the automotive industry is exploring electric compressors of large displacement. Compared with small and mid-size (displacement less than 33 cc) compressor, large (34-44 cc) and extra-large (45 cc and above) compressor products are used. This paper investigates the compressor sizing effect for heat pump (HP) system of A-Segment and D-Segment battery electric vehicles. The system performance is evaluated with large (34 cc) and extra-large (57 cc) compressors by considering energy efficiency, cabin thermal management and battery fast charging use cases.

Vehicle suspension parts are subjected to variable road loads, manufacturing process variation and high installation loads in assembly process. Seam welding can be considered as such process to connect more components and parts. Typical in a Mc Pherson suspension system stabilizer bar link is connected to the strut assembly through ball stud and clamped to a bracket welded to the outer strut tube. Cracks have been observed in the stabilizer bar link bracket welds of vehicles in the field, effecting the functionality of the suspension system. During preliminary phase of product development CAE assessment of the seam weld is carried out against road load data, if the design does not meet the targets enabler studies are carried out in an iterative approach. Various design variables (control factors) can be considered to carry out the iterations.

Design for Six Sigma (DFSS) is an essential tool and methodology for innovation projects to improve the product design/process and performance. This paper aims to present an application of the DFSS Taguchi Method for an automotive/vehicle component. High-Pressure Vacuum Assist Die Casting (HPVADC) technology is used to make Cast Aluminum Front Shock Tower. During the vehicle life, Shock Tower transfers the road high impact loads from the shock absorber to the body structure. Proving Ground (PG) and washout loads are often used to assess part strength, durability life and robustness. The initial design was not meeting the strength requirement for abusive washout loads. The project identified eight parameters (control factors) to study and to optimize the initial design. Simulation results confirmed that all eight selected control factors affect the part design and could be used to improve the Shock Tower's strength and performance.

A new method is demonstrated for rating the “severity” of a hypoid gear set duty cycle (revolutions at torque) using the intercept of T-N curve to support gearset selection and sizing decision across vehicle programs. Historically, it has been customary to compute a cumulative damage (using Miner's Rule) for a rotating component duty cycle given a T-N curve slope and intercept for the component and failure mode of interest. The slope and intercept of a T-N curve is often proprietary to the axle manufacturer and are not published. Therefore, for upfront sizing and selection purposes representative T-N properties are used to assess relative component duty cycle severity via cumulative damage (non-dimensional quantity). A similar duty cycle severity rating can also be achieved by computing the intercept of the T-N curve instead of cumulative damage, which is the focus of this study.