This study presents a dynamic model of a universal joint (U-Joint) with radial clearance, focusing on the rigid unilateral frictional contacts at the crosspiece and yoke interfaces. Unlike previous models that neglect crosspiece inertia and interface friction, this work incorporates these effects using a set-valued impact law based on Signorini's condition with Coulomb friction, capturing the complex non-smooth dynamics introduced by radial clearance. Numerical simulations of a 2 degrees-of-freedom (DOF) shaft system reveal the critical influence of clearance on U-Joint dynamic behavior, including impact-induced oscillations, quasi-periodic motion, and chaotic dynamics, which are essential for accurate driveline modeling and real-time control in automotive, aerospace, and precision medical applications.

This study presents the modeling and dynamic analysis of a universal joint (U-Joint) with radial clearance. The main focus is on the modeling of rigid unilateral frictional impacts at the crosspiece and input yoke contact interfaces. Previous literature on the modeling and dynamic analysis of U-Joints, neglect the crosspiece inertial characteristics and friction between yoke and crosspiece contact interface in the presence of mechanical clearances. While in studies without clearance the inertial and frictional dynamics can be neglected, they become essential for accurately capturing and understanding the non-smooth dynamics introduced by radial clearance between yoke and crosspiece. The impacts between yoke and crosspiece contact points are assumed to be rigid and characterized using a set-valued impact law based on Signorini’s condition combined with Stribeck friction law, capturing the complex contact interactions. The numerical simulations demonstrate the influence of small clearance on the dynamic response of U-Joints, revealing phenomena such as symmetrical double walled impact-induced oscillations, quasi-periodic oscillations, grazing bifurcations, and chaos.

The presence of clearances is inevitable in practical mechanisms. Components are designed to maintain optimal clearances between mating parts, enabling relative motion. There is extensive literature available on U-Joints from manufacturing tolerances perspective. In this work the emphasis is on clearances specifically existing between a yoke and trunnion, which affects the input/output motion characteristics. More specifically, the focus is on bifurcation analysis of systems with clearances between the yoke and crosspiece. To the best of authors knowledge literature is limited in this area. So, this effort will shed light on non-linear characteristics of motions in U-Joints. Clearances in U-Joint are categorized into axial and rotational type. Here we chose to explore the bifurcation characteristics associated with pure rotational type clearances and the effect of U-Joint inclination angle on the dynamical behavior of clearance between the yoke and the crosspiece of U-Joint. Several period-doubling route to chaos within a range of clearance sizes are observed. Other interesting bifurcations such as interior, boundary and basin-boundary crisis are also observed as a function of clearances.

Torsional vibration generated during operation of commercial vehicles can negatively affect the life of driveline components, including the transmission, driveshafts, and rear axle. Undesirable vibrations typically stem from off-specification parts, or excitation at one or more system resonant frequencies. The solution for the former involves getting the system components within specification. As for the latter, the solution involves avoiding excitation at resonance, or modifying the parameters to move the system’s resonant frequencies outside the range of operation through component changes that modify one, or more, component inertia, stiffness, or damping characteristics. One goal of the effort described in this article is to propose, and experimentally demonstrate, a physics-based gear-shifting algorithm that prevents excitation of the system’s resonant frequency if it lies in the vehicle’s range of operation. To guide that effort, analysis was conducted with a numerical simulation model incorporating nonlinear driveline dynamics resulting from engine operation (including misfire and cylinder deactivation), excitation from multiple universal joints, the transmission, and a vehicle speed feedback controller, a contribution the authors have not seen in the pre-existing literature. The experimentally validated simulation results demonstrate that the torsional oscillating mode corresponding to the torque converter or turbine exhibits sensitivity to clutch activation, and variations in system parameters. Consequently, variation in system parameters alters the natural frequency of the system, potentially aligning it with the vehicle’s operational frequency range in specific gear ranges. Experimental on-road tests, described here, demonstrate that for the truck-under-test one of the natural frequencies of the system is within the range of operation for gears 4, 5, and 6 for certain vehicle speeds. Resonance in these gears was successfully prevented, and experimentally demonstrated, by using the proposed algorithm without sacrificing the performance of the vehicle.

An algorithm is proposed for real-time detection of the natural frequencies of rotating shafts in the driveline using an onboard transmission control module (TCM). The algorithm, unlike previous methods, not only aims to detect the linear oscillating modes of the driveline but also incorporates the capability to identify both linear and nonlinear resonance modes. This algorithm is crucial for mitigating potential failures caused by cyclic loading, as it enables the detection of resonance modes beyond the linear range, which has been previously unexplored. By utilizing the fast Fourier transform (FFT) with respect to the revolutions of the transmission output shaft (order), the algorithm analyzes the vibration signals acquired from integrated transmission speed sensors. Experimental tests conducted on a medium-duty truck demonstrated the algorithm’s effectiveness in real-time execution on the transmission controller. Additionally, the algorithm’s capability to detect both linear and nonlinear resonance modes was validated through post-processing of additional data collected during these tests using signal processing tools. The results conclusively show that the proposed algorithm consistently and accurately detects the natural frequencies of rotating shafts in automatic transmissions across wide operating ranges.

This study presents an extended investigation into the dynamic behavior of a multidegree-of-freedom (DOF) driveline interconnected by a series of universal joints (U-joints). While previous studies have focused on the effects of rotational-type clearance within a single U-joint in a 2DOF shaft system—revealing bifurcation phenomena such as period-doubling routes to chaos and various crisis bifurcations—this work extends the analysis to a 3DOF driveline coupled with two U-joints arranged in a Z-type configuration, with a π/2 rad phase difference, which is previously not explored. The presence of multiple U-joints introduces additional holonomic constraints and nonsmooth nonlinearities, resulting in more complex dynamical behavior. This study highlights the significant influence of U-joint phasing on the dynamics of multijointed drivelines, particularly in the context of clearance-induced nonlinearities. Numerical bifurcation diagrams are constructed for driveline output states as functions of system parameters, and Poincaré mapping is used to characterize the presence of periodic and coexisting attractors, as well as strange chaotic attractors exhibiting fractal-like properties. The boundaries between periodic and chaotic regions are identified through the computation of basins of attraction for coexisting attractors and 2D parameter space. Furthermore, the study demonstrates that the driveline exhibits greater sensitivity to mechanical clearances in the downstream U-joint compared to the upstream joint, highlighting the critical role of U-joint phasing in torsional instability mitigation. These findings provide new insights into the nonlinear dynamics of driveline systems with multiple U-joints and clearances, paving the way for more accurate modeling and the development of robust design strategies.

Off-road vehicles are emphasizing brake thermal efficiency improvements to meet upcoming diesel emission standards set by the California Air Resources Board (CARB), aiming for enhanced engine and vehicle component efficiency. CARB is implementing regulations demanding a 90% reduction in oxides of nitrogen (NOx) emissions compared to current EPA Tier 4 standards, extending to off-highway vehicles by 2031. The experimental study described in this paper investigated how high-efficiency turbocharging (HET) and electric 48 V EGR pumping (EGRP) enable improved fuel efficiency in a 13.6 L off-road Diesel engine during steady-state operation. The integration of a 48 V EGR Pump enables the complete use of the high-efficiency turbo, encompassing both fuel reduction and NOx mitigation, at reduced engine delta pressure (exhaust-intake manifold pressure). Fuel consumption reductions in excess of 8% at low-speed/high-loads, nearly 5% on the torque curve at 1200 rpm, and 1.6%-3.1% in high-speed/high-load scenarios were demonstrated. NOx levels were generally similar to or lower than the baseline. Soot emissions remained comparable to or lower than the baseline. Open cycle efficiency (OCE) was improved across all points studied. Closed cycle efficiency improved under specific conditions, particularly at low-speed/high-load scenarios for which advanced injection timing could be used as a result of improved EGR flow control with the EGR pump. The OCE improvements were driven by reduced pumping work, with primary attribution to the high-efficiency turbocharger. The EGR pump played a pivotal role in maintaining engine-out NOx levels, especially under conditions where the conventional high-pressure EGR system would have been limited due to reduced pressure differentials between the intake and exhaust manifold (as a result of the high-efficiency turbocharging).

Torsional oscillations can pose a significant challenge in automatic transmissions, including those stemming from instabilities induced by friction in the clutch system during shifts. Examples include chatter, squeal, shudder, judder and squawk. Transmission squawk is more than just an annoying noise; it is a symptom of underlying issues that, if left unaddressed, can lead to significant structural failures. Squawk is a high-frequency torsional oscillation, predominantly induced due to a negative friction slope and the presence of a weakly damped oscillating mode in the transmission system. Although numerous passive methods are available to prevent the squawking of the clutch in automotive transmission, the significant drawback of passive methods is the limited duration of effectiveness. This paper particularly focuses on the mitigation of squawk using active control techniques. Since squawk occurs in clutch output, therefore, the output speed is used as the measured signal and clutch clamping force as the control action. The primary objective is to develop a control strategy that effectively dampens squawk oscillations while also minimizing control effort, a crucial aspect that has been overlooked in previous research on robust control of friction-induced vibrations (FIV) in context of automatic transmissions. The effectiveness of the designed controller is tested on an experimentally validated non-linear vehicle-level simulation model of a 9-speed automatic transmission. With the designed controller, the squawk oscillations are successfully suppressed. Comparisons with industrial routine PI controller are made to demonstrate the performance of mu-optimal controller in terms of minimal control effort and smoother clutch engagement.

The genesis of clutch noise, encompassing squeaks, chatter, shudders, or judders, predominantly arises from friction-induced vibrations. As time progresses, the degradation of the clutch friction lining manifests due to diverse factors, such as the smearing of surface irregularities, elevated transmission fluid temperatures, fluctuating axial pressure, or aggressive shifting. Consequently, the slope of the friction curves tends to assume a negative gradient, giving rise to adverse damping effects like self-excited oscillations or stick-slip oscillations within the clutch pack. A lesser-discussed phenomenon, known as squawking, occurs through analogous mechanisms discussed in this paper. This paper delves into investigating the occurrence of squawking noise observed in automatic transmission multi-disc clutches during low-speed up-shifts. The study discerns friction-induced vibrations as the primary contributor to squawk during the inertia phase of the clutch engagement cycle, a facet previously unidentified. During this phase, high-frequency weakly damped oscillating modes become self-excited due to the negative slope of the coefficient of friction versus slip speed curve. The coefficient of friction functions as negative damping during the inertia phase, where the energy dissipation from damping is insufficient to completely halt the oscillations, allowing them to persist approximately at the natural frequency until clutch lock-up. Experimental data validate the proposed model and hypothesis, with results closely aligning with numerical simulations. The paper concludes by offering practical suggestions to prevent and mitigate squawk in automatic transmission wet clutches, with the aim of enhancing overall performance and reducing undesirable noise.

This paper presents a generic simulation platform with two widely employed software, Simulink and Unreal, to simultaneously simulate the perception in virtual 3D scenarios and system dynamics of automated systems. The proposed CoSim framework improves the accuracy and reduces the development time of automation systems for agricultural crop harvesting and transfer. Strategies using either cameras or LiDAR are supported by the framework. To demonstrate the capability of the proposed CoSim tool, this paper simulates an automated offoading process conducted by a combine-tractor system with a closed-loop controller and a LiDAR-based perception system. The simulation results show that CoSim can be used for both system design and system evaluation.

This article performs a novel comparison of the life-cycle costs of the series and parallel architectures for plug-in hybrid electric vehicles. Economic viability is defined as having a payback period less than 2 years and number of battery replacements less than or equal to three over a vehicle life of 12 years along-with drivability and gradability constraints. Economic viability is compared for two plug-in hybrid electric vehicle applications (Medium-duty Truck and Transit Bus) using series and parallel architectures over multiple drivecycles, for three economic scenarios (viz. 2020, 2025 and 2030 where the fuel price, battery price and motor price are varied such that latter scenarios are more favorable for hybridization). One battery overnight recharge is assumed. The results demonstrate that by 2020 the plug-in hybrid electric vehicle transit buses are viable for the duty cycles Manhattan, Orange County, and China (Normal and Aggressive). By 2025, plug-in hybrid electric vehicle Class 6 trucks are viable for all duty cycles considered (Pick-up and delivery, Refuse and New York Composite). The parallel architectures generally require less than 50% of the initial cost of the series architecture, due to smaller motor sizes, driving earlier viability for parallel architectures. The transit bus scenarios generally achieve payback sooner than the medium-duty truck due to higher fuel cost savings, driving earlier viability for transit bus applications.

From the design space explored for series architecture plug-in hybrid electric vehicle transit buses by the authors, one powertrain and control design is selected to provide maximum benefit to investment ratio. Sensitivity analysis is performed for this powertrain configuration. Vehicle parameters (including vehicle mass, coefficient of drag, coefficient of rolling resistance), usage parameters (drivecycle, annual vehicle miles traveled, number of recharges in a day, recharge current, and battery temperature), and economic parameters (fuel price, motor price, and battery price) are varied to understand their effect on the number of required battery replacements, net present value, payback period, and fuel consumption reduction. It is shown that battery temperature has the most significant impact, particularly on the number of battery replacements and net present value and, as such, must be well controlled in practice. It is shown that to maintain the battery at 20°C, for ambient temperatures between −5°C and 45°C, 0.8–1.8% excess fuel is required across all drivecycles for the considered plug-in hybrid electric vehicle transit bus powertrain configuration. In addition, the well-to-wheel emissions of criteria pollutants resulting from the usage of this plug-in hybrid electric vehicle transit bus in Indiana and California are calculated and compared with the conventional transit bus, using the GREET (Greenhouse Gases, Regulated Emissions and Energy Use in Transportation) Model. With a single over night charge, the plug-in hybrid electric vehicle transit bus operating in either Indiana or California produces 50% less CO 2 and other greenhouse gases as compared to a conventional transit bus.

In this paper we present a mixed-integer linear program to represent the decision-making process for heterogeneous fleets selecting vehicles and allocating them on freight delivery routes to minimize total cost of ownership. This formulation is implemented to project alternative powertrain technology adoption and utilization trends for a set of line-haul fleets operating on a regional network. Alternative powertrain technologies include compressed (CNG) and liquefied natural gas (LNG) engines, hybrid electric diesel, battery electric (BE), and hydrogen fuel cell (HFC). Future policies, economic factors, and availability of fueling and charging infrastructure are input assumptions to the proposed modeling framework. Powertrain technology adoption, vehicle utilization, and resulting CO2 emissions predictions for a hypothetical, representative regional highway network are illustrated. A design of experiments (DOE) is used to quantify sensitivity of adoption outcomes to variation in vehicle performance parameters, fuel costs, economic incentives, and fueling and charging infrastructure considerations. Three mixed-adoption scenarios, including BE, HFC, and CNG vehicle market penetration, are identified by the DOE study that demonstrate the potential to reduce cumulative CO2 emissions by more than 25% throughout the period of study.

A System-of-Systems engineering methodology is used to project truck technology adoption behaviors of heterogeneous fleets operating over the U.S. line-haul freight transportation system. A constrained mixed-integer linear program is formulated to optimize total cost of ownership of regional fleets given vehicle highway performance, fleet operations, cost of energy, and freight demand. A design-of-experiments demonstrates adoption sensitivity to economic parameters and individual fleet management constraints. Validation results demonstrate the importance of modeling fleet heterogeneity to achieving 90% prediction accuracy of historical adoption of three different vehicle architectures across 12 representative fleets over a 11-year period.

Prior design optimization efforts do not capture the impact of battery degradation and replacement on the total cost of ownership, even though the battery is the most expensive and least robust powertrain component. A novel, comprehensive framework is presented for model-based parametric optimization of hybrid electric vehicle powertrains, while accounting for the degradation of the electric battery and its impact on fuel consumption and battery replacement. This is achieved by integrating a powertrain simulation model, an electrochemical battery model capable of predicting degradation, and a lifecycle economic analysis (including net present value, payback period, and internal rate of return). An example design study is presented here to optimize the sizing of the electric motor and battery pack for the North American transit bus application. The results show that the optimal design parameters depend on the metric of interest (i.e. net present value, payback period, etc.). Finally, it is also observed that the fuel consumption increases by up to 10% from "day 1" to the end of battery life. These results highlight the utility of the proposed framework in enabling better design decisions as compared to methods that do not capture the evolution of vehicle performance and fuel consumption as the battery degrades.

In this paper we present a model formulation to predict the powertrain and autonomy technology adoption in a line-haul freight transportation network. The vehicle adoption and utilization behaviors of fleets operating in the network are represented as a mixed integer linear program. Powertrain technologies evaluated include diesel engines, compressed and liquefied natural gas engines, diesel-electric hybrid, battery electric, and hydrogen fuel cell. Levels of autonomy introduced to the market include Level 2, Level 4, and Level 5 as defined by SAE standards. Simulated case scenarios are presented to demonstrate the utility of the model, with an emphasis on the types of insights that can be gained by analyzing both vehicle adoption and utilization. This in turn makes the proposed model a more effective tool for policy-making and other strategic decision-making.