Heavy Vehicle Aerodynamics: Massively-Separated Turbulent Flow & a Bio-Inspired Device

Dr. MacChesney’s doctoral studies focused on improvement of the state of the art in heavy vehicle aerodynamics through computational fluid dynamics methods. Through his research he has devised a drag reduction device inspired by the shape of a harbor seal whisker that reduces drag by up to 22%. Additionally, through application of a novel decomposition method he uncovered a hidden order within massively-separated turbulent flows with evidence that supports a centrifugal mechanism

Monte Carlo planning for active object classification

© 2017, Springer Science+Business Media New York. Classifying objects in complex unknown environments is a challenging problem in robotics and is fundamental in many applications. Modern sensors and sophisticated perception algorithms extract rich 3D textured information, but are limited to the data that are collected from a given location or path. We are interested in closing the loop around perception and planning, in particular to plan paths for better perceptual data, and focus on the problem of planning scanning sequences to improve object classification from range data. We formulate a novel time-constrained active classification problem and propose solution algorithms that employ a variation of Monte Carlo tree search to plan non-myopically. Our algorithms use a particle filter combined with Gaussian process regression to estimate joint distributions of object class and pose. This estimator is used in planning to generate a probabilistic belief about the state of objects in a scene, and also to generate beliefs for predicted sensor observations from future viewpoints. These predictions consider occlusions arising from predicted object positions and shapes. We evaluate our algorithms in simulation, in comparison to passive and greedy strategies. We also describe similar experiments where the algorithms are implemented online, using a mobile ground robot in a farm environment. Results indicate that our non-myopic approach outperforms both passive and myopic strategies, and clearly show the benefit of active perception for outdoor object classification

Improving driver comfort in commercial vehicles : modeling and control of a low-power active cabin suspension system

Comfort enhancement of commercial vehicles has been an engineering topic ever since the first trucks emerged around 1900. Since then, significant improvements have been made by implementing cabin (secondary) and seat suspensions. Moreover, the invention of the air spring and its application to the various vehicle's suspension systems also greatly enhanced driver comfort. However, despite these improvements many truck drivers have health related Problems, which are expected to be caused by their exposure to the environmental vibrations over longer periods of time. The most recent suspension improvements in commercial vehicles date back more than a decade and the possibilities for further improvements using passive devices (springs and dampers) seem nearly exhausted. Consequently, in line with developments in passenger cars, truck manufacturers are now investigating semi-active and active suspension systems. Herein, active suspensions are expected to give the best performance, but also come at the highest cost. Especially the high power consumption of market-ready devices is problematic in a branch where all costs need to be minimized. In this dissertation the field of secondary suspension design and controllable suspensions for heavy vehicles is addressed. More specifically, the possibilities for a low power active cabin suspension design are investigated. The open literature on this topic is very limited in comparison to that of passenger cars. However, as heavy vehicle systems are dynamically more challenging, with many vibration modes below 20 Hz, there is great research potential. The dynamic complexity becomes clear when considering the developed 44 degrees of freedom (DOF) tractor semi-trailer simulation model. This model is a vital tool for suspension analysis and evaluation of various control strategies. Moreover, as it is modular it can also be easily adapted for other related research. The main vehicle components all have their own modules. So, for example, when evaluating a new cabin suspension design, only the cabin module needs to be replaced. The model has been validated using extensive tests on a real tractor semi-trailer test-rig. The control strategy is a key aspect of any active suspension system. However, the 44 DOF tractor semi-trailer model is too complex for controller design. Therefore, reduced order models are required which describe the main dynamic properties. A quarter truck heave-, half truck roll-, and half truck pitch-heave model are developed and validated using a frequency-domain validation technique and the test-rig measurements. The technique is based on a recently developed frequency domain validation method for robust control and adapted for non-synchronous inputs, with noise on the input and output measurements. The models are shown to give a fair representation of the complex truck dynamics. Furthermore, the proposed validation method may be a valuable tool to obtain high quality vehicle models. As a first step, in search of a low power active cabin suspension system, various suspension concepts are evaluated under idealized conditions. From this evaluation, it follows that the variable geometry active suspension has great potential. However, the only known physical realization - the Delft Active Suspension - suffers from packaging issues, nonlinear stiffness characteristics, fail-safe issues and high production cost. Recently, a redesign - the electromechanical Low-Power Active Suspension (eLPAS) - was presented, which is expected to overcome most of these issues. This design is modeled, analyzed and a controller is designed, which can be used to manipulate the suspension force. Feasibility of the design is demonstrated using tests on a hardware prototype. Finally, the validated reduced order models are used to design suitable roll and pitch-heave control strategies. These are evaluated using a combination of the 44 DOF tractor semi-trailer and eLPAS models. Four eLPAS devices are placed at the lower corners of the cabin and modal input-output decoupling is applied for the controller implementation. It is shown, that driver comfort and cabin attitude behavior (roll, pitch and heave when braking, accelerating or steering) can be greatly improved without consuming excessive amounts of energy. So, overall these results enforce the notion that the variable geometry active suspension can be effectively used as low power active cabin suspension. However, there are still some open questions that need to be addressed before this design can be implemented in the next generation commercial vehicles. Durability and failsafe behavior of the eLPAS system, as well as controller robustness to variations in the vehicle parameters and environmental conditions, are some of the topics that require further study