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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.

As electrification of powertrains is progressing, diversification of hybrid powertrains increases. This generally imposes the challenge for a supervisory controller of how to optimally control the torque of the electric machine(s). Architectures, which have at least one belt driven electric machine, are an essential part of the portfolio. This paper describes a strategy on how to include the losses of the belt device in the determination of optimal electric machine torque command. It first depicts a physics-based method for controlling optimal electric machine torque command for systems without a belt connected electric machine. This method considers the constraints of the electric machine(s) as well as the power limitations from the electric devices, which supply power to the motors.

This paper focuses on an inherent problems of active damping control prevalent in contemporary hybrid torque controls. Oftentimes, a supervisory torque controller utilizes simplified system models with minimal system states representation within the optimization problem, often not accounting for nonlinearities and stiffness. This is motivated by enabling the generation of the optimum torque commands with minimum computational burden. When inherent lash and stiffness of the driveline are not considered, the resulting command can lead to vibrations and oscillations in the powertrain, reducing performance and comfort. The paper proposes a Linear Quadratic Integral (LQI)-based compensator to be integrated downstream the torque supervisory algorithm, which role is to shape transient electric machine torques, compensating for the stiffness and backlash present in the vehicle while delivering the driver-requested wheel torque.

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.

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.

Water fording events are one of the most challenging situations that vehicles undergo during their lifetime. During these events the underbody components (e.g. Front fascia, Bellypan, wheel liner etc.) are subject to very high loads. Typically, vehicle water fording tests are performed for various depths of water at prescribed vehicle speeds. Water fording tests are usually carried out during the proto phase of the vehicle development program to ensure acceptable performance. If issues are discovered, making changes to the fascia or body panels are typically very expensive. To avoid late changes, a fully virtual methodology was developed to facilitate vehicle water fording performance. The simulation is targeted to evaluate multiple aspects such as air induction system and estimation of hydrodynamic loads on body panel components.

Many chassis and powertrain components in the transportation and automotive industry experience multi-axial cyclic service loading. A thorough load-history leading to durability damage should be considered in the early vehicle production steps. The key feature of rubber fatigue analysis discussed in this study is how to define local critical location strain time history based on nominal and complex load time histories. Material coupon characterization used here is the crack growth approach, based on fracture mechanics parameters. This methodology was utilized and presented for a truck engine mount. Temperature effects are not considered since proving ground (PG) loads are generated under isothermal high temperature and low frequency conditions without high amounts of self-heating.

The Los Angeles City Traffic (LACT) brake test is well known acclaimed procedure used by many vehicle manufacturers to assess the brake pad wear behavior and to investigate the Noise, Vibration and Harness (NVH) performance of the brake system. The LACT driving route consists of a set of real-world driving conditions, which has been considered representative of the US passenger vehicle market. The scope of this study is to mimic the LACT test using finite element analysis (FEA) to calculate the wear displacement based on Rhee’s theory. The Leading-edge and trailing edge of the brake pad’s wear tendency is also predicted from the simulation. The finite element model for wear simulation consists of brake system viz., Rotor, Knuckle, Pads, Anchor bracket, Piston, and Caliper.

Fasteners, commonly used in automotive industry, play an important role in the safety and reliability of the vehicle structural system. In practical application, bolted joints would never undergo fully reversed loading; there always will be positive mean stress on bolt. The mean stress has little influence on the fatigue life if the maximum stress is lower than a threshold which is near the yield stress of the bolt. However, when the sum of the mean stress and the stress amplitude exceeds the threshold, the endurance limit stress amplitude decreases fast as the mean stress increases. The purpose of this paper is to research the fatigue endurance limit of a fastener and establish the threshold for safe design in automotive application. In order to obtain the fatigue endurance limit at different mean stress levels, various mechanical tests were performed on M12x1.75 and M16x1.5 Class 10.9 fasteners using MTS test systems.

Reducing emissions and the carbon footprint of our society have become imperatives requiring the automotive industry to adapt and develop technologies to strive for a cleaner sustainable transport system and for sustainable economic prosperity. Electrified hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) and range extender powertrains provide potential solutions for reducing emissions, but they present challenges in terms of thermal management. A key requirement for meeting these challenges is accurately to predict the thermal loading and temperatures of an internal combustion engine (ICE) quickly under multiple full-load and part-load conditions. Computational Fluid Dynamics (CFD) and thermal survey database methods are used to derive thermal loading of the engine structure and are well understood but typically only used at full-load conditions.

Cargo box is one of the indispensable structures of a pickup truck which makes it capable of transporting heavy cargo weights. This heavy cargo weight plays an important role in durability performance of the box structure when subjected to road load inputs. Finite element representation for huge cargo weight is always challenging, especially in a linear model under dynamic proving ground road load durability analysis using a superposition approach. Any gap in virtual modeling technique can lead to absurd cargo box modes and hence durability results. With the existing computer aided engineering (CAE) approach, durability results could not correlate much with physical testing results. It was crucial to have the right and robust CAE modeling technique to represent the heavy cargo weight to provide the right torsional and cargo modes of the box structure and in turn good durability results.

Accurate prediction of in-vehicle powertrain bounce mode is necessary to ensure optimum responses are achieved at driver’s touch points during 4post shake or rough road shake events. But, during the early stages of vehicle development, building a detailed vehicle finite element (FE) model is not possible and often powertrain bounce modes are computed assuming the powertrain to be a stand-alone unit. Studies conducted on FE models of a large SUV with body on frame architecture showed that the stand-alone approach overestimates the powertrain bounce mode. Consequently, there is a need for a simplified version of vehicle model which can be built early on to compute powertrain modes. Previously, representing all the major components as rigid entities, simplified unibody vehicle models have been built to compute powertrain modes. But such an approach would be inaccurate here, for a vehicle with body on frame architecture due to the flexible nature of the frame (even at low frequencies).

This paper focuses on the conjugate heat transfer analysis of an I4 engine, and discusses optimization of the coolant passages in engine coolant jackets. Direct Optimization approach integrates an optimizer with the numerical solver. This method of optimization is compared with a metamodel-based optimization in which a metamodel is generated to aid in finding an optimal design. The direct optimization and metamodel approaches are compared in terms of their accuracy, and execution time.

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 complexities involved in an optimization problem at a system level require knowledge base that has information on different approaches and customization of these approaches to a specific class of the optimization problems. One approach that is commonly used is the metamodel based design optimization. The metamodel is 1) a conceptual model for capturing, in abstract terms, essential characteristics of a given optimization problem, and 2) a schema of sufficient formality to enable the problem modeled to be serialized to statements in a concrete optimization language [1]. Optimization is performed based on this metamodel. This metamodel approach has been proven effective and accurate in providing the global optimum. Depending upon the computational hardware availability in an organization, the metamodel based optimization could be much faster way of achieving the optimized solution. However, the accuracy of the optimization is highly dependent on the quality of metamodel generated.

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.

Vibrations affect vehicle occupants and should be prevented early in design process. Powertrain (PT) wiggle is one of the well-known issues. It is the 3rd order lateral vibration, forced by half shaft inner LH/RH plunging tripod joints [1,2]. Lateral PT resonance (7-15Hz) occurs at certain vehicle speed during acceleration and may excite lateral, pitch and roll PT modes. Typically, PT wiggle occurs in speed range of 5-25kph. Vibration is noticeable on driver and passenger seats mostly in lateral direction. The inner half shaft joints are the major source of vibration. Unfortunately, existing MBD tools like Adams [3] are missing detailed tripod joint representation because of complex mechanical interactions inside the joint. At least three sliding contacts between tripod rollers and joint housing, lubricant inside the can and combination of rotation and plunging make the modeling too complicated.

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.