Aiming at the problem of poor robustness after the combination of lateral kinematics control and lateral dynamics control when an autonomous vehicle decelerates and changes lanes to overtake at a certain distance. This paper proposes a trajectory determination and tracking control method based on a PI-MPC dual algorithm controller. To describe the longitudinal deceleration that satisfies the lateral acceleration limit during a certain distance of lane change, firstly, a fifth-order polynomial and a uniform deceleration motion formula are established to express the lateral and longitudinal displacements, and a model prediction controller (MPC) is used to output the front wheel rotation angle. Through the dynamic formula and the speed proportional-integral (PI) controller to control and adjust the brake pressure.
According to the European Environment Agency, air pollution is the biggest environmental health risk in Europe. Since traffic is one of the main contributors of fine dust, technical solutions are necessary to reduce the particulate emission footprint of vehicles. Also the Health Effects Institute hosted recently an international workshop on non-tailpipe emissions. Brake dust filtration concepts have proven to be a promising solution to significantly reduce fine dust emissions from brakes directly at the source. While CFD simulations for inner-ventilated brakes have become state-of-the-art, a holistic models from particle generation and emission to particle dynamics in the vicinity of the brake is not yet available. However, a good modeling approach of particle tracks is essential to predict filtration efficiencies of brake dust particle filters.
The cabin cool down performance is influenced by heat load, AC system components and Air handling components. The air handling components are AC duct, vane and vent. Design of AC duct vane plays a crucial role in the airflow directivity in cabin which enhances the cabin cool down performance. Simulations are carried out by rotating the vanes manually and requires post process for every iteration. It leads to more time consuming and more number of simulations to achieve the target value. Research articles focusing on automation and optimization of vane articulation studies are scanty. Thus, the objective of this work is to execute the vane articulation study with less manual intervention. A parametric approach is developed by integrating ANSA and ANSYS FLUENT tools. With Direct Fit Morphing and DoE study approach from ANSA delivers the surface mesh model for the different vane angle configurations.
In automotive product development, design and development of the chassis plays an important role since all the internal and external loads pass through the vehicle chassis. Durability, NVH, Dynamics as well as overall vehicle performance is dependent on the chassis structure. Even though passenger vehicle chassis has a ladder frame or a monocoque construction, small commercial vehicle chassis is a hybrid chassis with the cabin welded to the ladder frame. As mileage is critical for sale of SCVs, making a light-weight chassis is also important. This creates a trade-off between the performance and weight which needs to be optimized. In this study, a parametric beam model of the ladder frame & the cabin of the vehicle is created in COMSOL Multiphysics. The structure has been parameterized into the long member & crossmember geometry & sections. The model calculates the first 12 natural frequencies, global stiffness, and weight.
Orientation of the spring-damper system in a suspension geometry is a critical but hidden factor in vehicle performance characteristics. Spring and damper mounting characteristics are the significant factors to ensure proper contact of the tire with the ground, maintaining ride height, minimizing forces on spring, smooth ride, and driver comfort. Determining the spring orientation is conventionally a long and iterative process that involves computational simulations and processing of analytical expressions, which should align with the practical vehicle constraints. Due to numerous possible orientations, the designer would randomly pick the orientation and do the simulation, which reduces the reliability of the solution and the better solutions remain unexplored. This paper proposes a new methodology to optimize spring damper orientation in a suspension geometry using a genetic algorithm in Python Programming Language.