This study presents performance and emissions data of an Otto cycle mono-cylinder combustion engine operating with two different compression rates and several mixtures of anhydrous ethanol fuel and water. The instrumented engine was mounted on a dynamometer with the ignition point and injection fuel advance calibrated to obtain the maximum torque and mixture in stoichiometric conditions. Characteristic engine performance parameters and emission fractions from its exhaust system were acquired from 2,000 rpm to 4,000 rpm with fuel mixtures of up to 50% water content. To our knowledge, data on this extreme operating condition are not available in the literature.

This article addresses the yaw stability of articulated vehicles by assessing the influence of the road-tire friction coefficient on the convergence region of a particular equilibrium condition. In addition, the boundaries of this region are compared to the boundaries of the non-jackknife and non-rollover regions to distinguish the instability phenomenon, jackknife or roll-over, responsible for this delimitation. The vehicle configuration considered in this analysis is composed by one tractor unit and one towed unit connected through an articulation point, for instance, a tractor-semitrailer combination. A nonlinear articulated bicycle model with four degrees of freedom is used together with a nonlinear lateral force tire model. To estimate the convergence region, the phase trajectory method is used. The equations of motion of the mathematical model are numerically integrated for different initial conditions in the phase plane, and the state orbits are monitored in order to verify the convergence point and the occurrence of instability events. In all cases, the longitudinal force on each tire, such as traction and braking, is not considered. The results show the existence of convergence regions delimited only by jackknife events, for low values of the friction coefficient, and only by rollover events, for high values of the friction coefficient. Moreover, the transition between these two conditions as the friction coefficient is changed is graphically presented. The main contributions of this article are the identification of the abrupt reduction of the convergence region as the value of the friction coefficient increases and the distinction of the instability events, jackknife or rollover, that define the boundaries of the convergence region.

Vehicle dynamics simulation is an essential stage of product development. It is a low cost alternative to the expensive and time-consuming experimental tests performed during the design phase. The ability to accurately predict the dynamics of vehicles can, for instance, provide useful information about their stability characteristics. Yaw instability, in particular, can cause divergent yaw behavior in conventional passenger cars and jackknife in articulated vehicles, like tractor-semitrailer combinations. These instabilities are associated with safety issues since their occurrence can cause accidents with fatal losses, injuries and property damage. Therefore, the development of vehicle models and simulation environments is necessary. This paper presents the open source package Vehicle Dynamics - Lateral. Developed using the object oriented programming paradigm, the package provides a collection of vehicle and tire models, represented by a set of base parameters and characteristic functions covering both simple and articulated vehicle simulations, as well as specific graphics generation. The package is hosted on GitHub, an online platform where software code can be shared and collaboratively developed. The goal of the package is to serve as a free, open and expandable toolbox for vehicle dynamics studies, as an academic alternative to the high cost closed commercial programs. This approach ensures thorough access to the source code and allows researchers and developers to verify all details of the implementation, as well as collaborate to the project. The code is written in MATLAB, a well-spread programming language with a significant number of adepts both in academia and industry.

This study introduces and experimentally validates an autonomous driving platform for off-road $8\times 4$ heavy-duty trucks, aimed at sugarcane harvesting operations. The system integrates a minimally invasive drive-by-wire interface for throttle, braking, and steering; a GNSS-based localization module; and a lightweight perception suite comprising a 2D LiDAR and a monocular camera. A modular ROS2-based architecture supports real-time perception, planning, and control. The platform was tested on an off-road track in Brazil across eight driving scenarios, including straight paths, curves, and obstacle avoidance at varying speeds. A spatial evaluation framework was implemented using arc-length reparameterization and KD-Tree nearest-neighbor matching to compare actual and reference trajectories. Metrics included lateral and heading RMSE, IAE, ITAE, jerk, and obstacle clearance. Results showed consistent high lateral tracking accuracy, with RMSE reaching 0.15 m in straight segments and remaining below 1.0 m in most complex scenarios. Scenario T8, involving curvature and obstacle deviation, surpassed this threshold due to increased control demands. Across 40 runs, heading RMSE remained below 10°, obstacle clearance above 1.5 m, and jerk below 0.5 m/s3. Geometrically modeled references yielded more stable heading control, while manually recorded paths resulted in smoother dynamic profiles. Statistical analysis confirmed that increased trajectory complexity degrades performance. Scenario T6 outperformed others in lateral stability, though results were statistically like T1 under simpler conditions. The platform demonstrated reliable tracking and real-time operation in scenarios representative of off-road agricultural tasks. Future work will focus on mitigating GNSS latency, improving post-obstacle recovery, and integrating sensor redundancy and adaptive planning to enhance deployment in agricultural logistics.