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Countless articles and publications3,4,5 have documented and proven the efficacy, benefits and value of operating within a lean system. Furthermore, there exists common agreement amongst leading organizations successfully implementing a lean system that in order to do so it must take into consideration the entire enterprise, that is, from supplier to customer and everything in between6. One of the core issues this paper addresses is when the optimal time is to train and educate the people who currently have, or will have, influence over the ‘enterprise’.

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.

A challenge for the aerodynamic optimization of trucks is the limited availability of wind tunnels for testing full scale trucks. FAW wants to introduce a development process which is mainly based on CFD simulation in combination with some limited amount of wind tunnel testing. While maturity of CFD simulation for truck aerodynamics has been demonstrated in recent years, a complete validation is still required before committing to a particular process. A 70% scale model is built for testing in the Shanghai Automotive Wind Tunnel Center (SAWTC). Drag and surface pressures are measured for providing a good basis for comparison to the simulation results. The simulations are performed for the truck in the open road driving condition as well as in an initial digital model of the aerodynamic wind tunnel of SAWTC. A full size truck is also simulated in the open road driving condition to understand the scaling effect.

Autonomous vehicle navigation, both global and local, makes use of large amounts of multifactorial data from onboard sensors, prior information, and simulations to safely navigate a chosen terrain. Additionally, as each mission has a unique set of requirements, operational environment and vehicle capabilities, any fixed formulation for the cost associated with these attributes is sub-optimal across different missions. Much work has been done in the literature on finding the optimal cost definition and subsequent mission pathing given sufficient measurements of the preference over the mission factors. However, obtaining these measurements can be an arduous and computationally expensive task. Furthermore, the algorithms that utilize this large amount of multifactorial data themselves are time consuming and expensive.

Motivated by accurate representations in gear dynamics models, this work analyzes the force-deflection relationship between spur gear pairs when the gear teeth have tooth root cracks. A finite element/contact mechanics approach is used to accurately capture the elastic deformations of the gear mesh incorporating kinematic gear motion; elastic deflections of the teeth, root, and blank; and elastic contact between the mating gear teeth. Tooth root crack damage of fixed sizes are analyzed, and the resulting static transmission error and mesh stiffness are calculated. These FE/CM model outputs are relatively insensitive to important gear crack geometry, including the initial crack location, the path it follows, and its final location. Crack-induced changes in static transmission error and mesh stiffness are driven by the remaining amount of the tooth that is healthy. Calculations of average-slope and local-slope mesh stiffness are included because both are used in gear dynamic models.

A finite element/contact mechanics (FE/CM) method is used to determine the tooth contact forces, static transmission error, and tooth pair stiffnesses for spur gear pairs that have pitting damage. The pitting damage prevents portions of the tooth surface from carrying load, which results in meaningfully different contact pressure distribution on the gear teeth and deformations at the mesh. Pits of elliptical shape are investigated. Parametric analyses are used to investigate the effect of pit width (along the tooth face) and height (along the tooth profile) on the gear tooth mesh interface. Pitting damage increases static transmission error and decreases tooth pair stiffness. Tooth contact forces differ only in the portions of the mesh cycle when multiple pairs of teeth are in contact and share the transmitted load. Pitting damage does not change the loads when only a single pair of teeth are in contact.

As the industry moves further into the automotive age, the failure of the cup during the transportation of the parts during the assembly process is costly. Among them, the effective contact area of the suction cup could influence the significant availability of the pressure, which is necessary to investigate the truth. The essential objective for this research is trying to improve the effectiveness of the suction cups during gripers work in company’s industry. In this research, the real work condition is simulated by the experimental setup to find the influence of the effective contact area. In this paper, the proper methodology to measure the effective area by testing different size cups under different conditions is described. The results are verified by the digital image correlation (DIC) technique.

The hole stretchability of two Aluminum Alloys (AA6111 and AA6022) are studied by using a two stages integrated finite element framework where the edge geometry and edge damages from the hole piercing processes were considered in the subsequent hole expansion processes. Experimentally it has been found that AA6022 has higher hole expansion ratios than those of AA6111. This observation has been nicely captured by finite element simulations. The main cause of differences have been identified to the volume fractions of the random distributed second phase hard particles which play a critical role in determining the fracture strains of the materials.

With the rapid development of computing technology, high-speed photography system and image processing recently, in order to meet growing dynamic mechanical engineering problems demand, a brief description of advances in recent research which solved some key problems of dynamic photo-elastic method will be given, including:(1) New digital dynamic photo-elastic instrument was developed. Multi-spark discharge light source was replaced by laser light source which was a high intensity light source continuous and real-time. Multiple cameras shooting system was replaced by high-speed photography system. The whole system device was controlled by software. The image optimization collection was realized and a strong guarantee was provided for digital image processing. (2)The static and dynamic photo-elastic materials were explored. The new formula and process of the dynamic photo-elastic model materials will be introduced. The silicon rubber mold was used without the release agent.

A comprehensive formulation is presented for the dynamics of a rotating flexible crankshaft coupled with the dynamics of an engine block through a finite difference elastohydrodynamic main bearing lubrication algorithm. The coupling is based on detailed equilibrium conditions at the bearings. The component mode synthesis is employed for modeling the crankshaft and block dynamic behavior. A specialized algorithm for coupling the rigid and flexible body dynamics of the crankshaft within the framework of the component mode synthesis has been developed. A finite difference lubrication algorithm is used for computing the oil film elastohydrodynamic characteristics. A computationally accurate and efficient mapping algorithm has been developed for transferring information between a high - density computational grid for the elastohydrodynamic bearing solver and a low - density structural grid utilized in computing the crankshaft and block structural dynamic response.

Experiments were carried out on a straight pipe extension of an exhaust port of a multi-cylinder, spark-ignition engine to investigate the axial variation of the steady-state surface heat transfer. Local, steady-state, surface heat flux measurements were made at five different stations on the test section. Based on an optimization procedure developed in this study, the heat-flux measurements obtained for axial distances x / D > 2, were found to be correlated very well (R2 = 0.95) by an equation in the form of an entrance length correction, which is a function solely of x / D, multiplied by the Sieder-Tate convective heat transfer correlation; a correlation valid for fully-developed, steady-state, turbulent, pipe flows. Most importantly, this paper provides strong evidence that the observed heat transfer augmentation in the engine exhaust system is due solely to entrance effects and not due to flow fluctuations, which was the accepted cause.

Mobility in the automotive and transportation sectors has been experiencing a period of unprecedented evolution. A growing need for efficient, clean and safe mobility has increased momentum toward sustainable technologies in these sectors. Toward this end, battery electric vehicles have drawn keen interest and their market share is expected to grow significantly in the coming years, especially in light-duty applications such as passenger cars. Although the battery electric vehicles feature high performance and zero tailpipe emission characteristics, economic and technical issues such as battery cost, driving range, recharging time and infrastructure remain main hurdles that need to be fully addressed. In particular, the low power density of the battery limits its broad adoption in heavy-duty applications such as class 8 semi-trailer trucks due to the required size and weight of the battery and electric motor.

This paper presents a nonlinear model predictive controller (NMPC) coupled with a pre-trained reinforcement learning (RL) model that can be applied to lateral control tasks for autonomous vehicles. The past few years have seen opulent breakthroughs in applying reinforcement learning to quadruped, biped, and robot arm motion control; while these research extend the frontiers of artificial intelligence and robotics, control policy governed by reinforcement learning along can hardly guarantee the safety and robustness imperative to the technologies in our daily life because the amount of experience needed to train a RL model oftentimes makes training in simulation the only candidate, which leads to the long-standing sim-to-real gap problem–This forbids the autonomous vehicles to harness RL’s ability to optimize a driving policy by searching in a high-dimensional state space.

This paper presents the development of surrogate models (metamodels) for evaluating the bearing performance in an internal combustion engine without performing time consuming analyses. The metamodels are developed based on results from actual simulation solvers computed at a limited number of sample points, which sample the design space. A finite difference bearing solver is employed in this paper for generating information necessary to construct the metamodels. An optimal symmetric Latin hypercube algorithm is utilized for identifying the sampling points based on the number and the range of the variables that are considered to vary in the design space. The development of the metamodels is validated by comparing results from the metamodels with results from the actual bearing performance solver over a large number of evaluation points. Once the metamodels are established they are employed for performing probabilistic analyses.

The door closing effort is a quality issue concerning both automobile designers and customers. This paper describes an Excel based mathematical model for predicting the side door closing effort in terms of the required minimum energy or velocity, to close the door from a small open position when the check-link ceases to function. A simplified but comprehensive model is developed which includes the cabin pressure (air bind), seal compression, door weight, latch effort, and hinge friction effects. The flexibility of the door and car body is ignored. Because the model simplification introduces errors, we calibrate it using measured data. Calibration is also necessary because some input parameters are difficult to obtain directly. In this work, we provide the option to calibrate the hinge model, the latch model, the seal compression model, and the air bind model. The door weight effect is geometrically exact, and does not need calibration.

This paper presents an optimal control co-design framework of a parallel electric-hydraulic hybrid powertrain specifically tailored for heavy-duty vehicles. A pure electric powertrain, comprising a rechargeable lithium-ion battery, a highly efficient electric motor, and a single or double-speed gearbox, has garnered significant attention in the automotive sector due to the increasing demand for clean and efficient mobility. However, the state-of-the-art has demonstrated limited capabilities and has struggled to meet the design requirements of heavy-duty vehicles with high power demands, such as a class 8 semi-trailer truck. This is especially evident in terms of a driving range on one battery charge, battery charging time, and load-carrying capacity. These challenges primarily stem from the low power density of lithium-ion batteries and the low energy conversion efficiency of electric motors at low speeds.

A fast and accurate journal bearing elastohydrodynamic analysis is presented based on a finite difference formulation. The governing equations for the oil film pressure, stiffness and damping are solved using a finite difference approach. The oil film domain is discretized using a rectangular two-dimensional finite difference mesh. In this new formulation, it is not necessary to generate a global fluidity matrix similar to a finite element based solution. The finite difference equations are solved using a successive over relaxation (SOR) algorithm. The concept of “Influence Zone,” for computing the dynamic characteristics is introduced. The SOR algorithm and the “Influence Zone” concept significantly improve the computational efficiency without loss of accuracy. The new algorithms are validated with numerical results from the literature and their numerical efficiency is demonstrated.

Although the performance of CNC machines is accurate, unavoidable human errors at the part loading position have serious repercussions on engine performance. In the present paper the authors would like to develop an algorithm for error compensation when the tool movement is unrestricted in space. The new solution algorithm will be in terms of the known initial system variables such as the part loading errors, drill tool inclinations, location of spindle etc. This modified paper employs the same principles of inverse kinematics as done in the earlier paper wherein a faulty compound-hole angle axis in space caused by the translational and rotational errors at the part loading position is identified with an imaginary true axis in space by enforcing identity through a modified machine axes taking into effect inclination of the drill tool in space. In the absence of any specific application, this algorithm is verified on Solid Works a commercial CAD tool and found to be correct.

Proper valve angles and concentric valve seats are critical to performance of an engine. If the valve seat were not right, the valve is not going to seat properly resulting in reduced power output. Although the performance of CNC machines is accurate, unavoidable human errors at the part loading position have serious repercussions on engine performance. A solution algorithm presented in this paper employs the principles of inverse kinematics wherein a faulty compound-hole angle axis in space caused by the translational and rotational errors at the part loading position is identified with an imaginary true axis in space by enforcing identity through a modified machine axes.

Predicting the optimum performance parameters of an automotive cyclone particle separator (separation efficiency and pressure drop) using computational fluid dynamics by varying its geometrical parameters is challenging and a time consuming process due to the highly swirling nature of the flow. This study presents results of three investigations of the performance and design of a cyclone separator: a sensitivity analysis, deterministic optimization and a reliability based design optimization. All three cases involved variation of four geometric parameters that characterize the design of the cyclone.