Advances in Mechanical Systems Dynamics 2020

The fundamentals of mechanical system dynamics were established before the beginning of the industrial era. The 18th century was a very important time for science and was characterized by the development of classical mechanics. This development progressed in the 19th century, and new, important applications related to industrialization were found and studied. The development of computers in the 20th century revolutionized mechanical system dynamics owing to the development of numerical simulation. We are now in the presence of the fourth industrial revolution. Mechanical systems are increasingly integrated with electrical, fluidic, and electronic systems, and the industrial environment has become characterized by the cyber-physical systems of industry 4.0. Within this framework, the status-of-the-art has become represented by integrated mechanical systems and supported by accurate dynamic models able to predict their dynamic behavior. Therefore, mechanical systems dynamics will play a central role in forthcoming years. This Special Issue aims to disseminate the latest research findings and ideas in the field of mechanical systems dynamics, with particular emphasis on novel trends and applications

High-powered electric motorcycle integrated performance studies

Electric vehicles and low carbon technology are currently at the forefront of research due to the need to rapidly reduce global carbon emissions. Significant effort has been invested into the improvement of electric cars but comparatively little for electric motorcycles, especially high-performance electric motorcycles. To achieve high-performance it is important to capture relevant design trade-offs and plan for vehicle optimisation prior to starting detailed design. These design trade-offs typically involve optimal sizing of the vehicle battery, electric motor, and motor drive, as well as the determination of the optimum lift-to-drag ratio. A full vehicle analysis including pertinent mechanical and electrical elements is required to perform this properly, as the system is highly interdependent. Existing models are shown to be lacking in key areas, notably the integration of an appropriate battery model, a realistic electric motor model (reflecting modern high-performance electric motorcycle design practices), and an appropriate tyre model, amongst other issues. The work in this thesis builds and validates a full vehicle model of a modern high-performance electric motorcycle. This is accomplished by first developing a rigid body dynamics motorcycle model that includes a full tyre model, the effects of downforce, differing front and rear tyres, and front-wheel drive. Further work is then undertaken to increase the depth and suitability of the electric powertrain modelling for high-performance electric motorcycles. Here, the battery thermal and electrical responses are modelled as well as the powertrain torque response, including saturation and loss modelling of the motor, motor drive and final drive. To validate these models both motor dynamometer testing and battery cycle testing is performed. An accelerated battery testing procedure is also developed to reduce the time required to properly evaluate and characterise test cells for performance evaluation. Having developed the vehicle model, a lap simulation procedure is then developed, implemented, and validated. Validation uses lap data acquired at multiple events including the Isle of Man TT Zero, Pikes Peak International Hillclimb (PPHIC) and Elvington Airfield Land speed record attempts. The lap simulation is then extended to include the effects of energy deployment strategy on lap time. This includes a different methodology for designs that are limited by the battery thermal performance and those that are not. This deployment strategy implementation is shown to significantly affect lap time. The work continues with lap time simulations of the Isle of Man TT Zero and PPHIC, investigating the respective influence of energy management on battery sizing. This shows that it is important to include the energy management strategy into the design evaluation and that the energy management trade-offs are specific to each race event. Additionally, analysis shows that situations, where battery temperature management strategies dominate energy management strategies, should be avoided by the proper design of a battery cooling system. This is because the penalty associated with reducing battery temperature through power and velocity limitations is higher than that of including sufficient cooling. The lap time sensitivity to mass, motor inertia, winglet lift-to-drag ratios and other design variables are explored with recommendations made for the Isle of Man TT Zero race and PPHIC. It is shown that by properly including representations of the underlying physics using a holistic modelling approach, and utilising a quantifiable objective, the relative contribution of individual elements can be quantified and directly compared. The significance of this from a full vehicle design standpoint is large as now vehicle development can be accurately targeted into areas that provide significant benefit. This can greatly improve the efficiency of the development process and the ultimate performance of the motorcycle

The Dynamics and Control of a Three-Wheeled Tilting Vehicle

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

The dynamics and control of a three-wheeled tilting vehicle

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Eco-Driving planification profile for electric motorcycles

Los perfiles de Eco-Driving son algoritmos capaces de utilizar información adicional para crear recomendaciones o limitaciones sobre las capacidades del conductor. Aumentan la autonomía del vehículo, pero actualmente su uso no está relacionado con la autonomía requerida por el conductor. Por esta razón, en este trabajo, el desafío de la conducción ecológica se traduce en un controlador óptimo de dos capas diseñado para vehículos eléctricos puros. Este controlador está orientado a asegurar que la energía disponible sea suficiente para completar un viaje demandado, agregando límites de velocidad para controlar la tasa de consumo de energía. Se exponen y analizan los modelos mecánicos y eléctricos requeridos. La función de costo está optimizada para corresponder a las necesidades de cada viaje de acuerdo con el comportamiento del conductor, el vehículo y la información de la trayectoria. El controlador óptimo propuesto en este trabajo es un controlador predictivo de modelo no lineal (NMPC) asociado a una optimización unidimensional no lineal. La combinación de ambos algoritmos permite aumentar alrededor de un 50% la autonomía con una limitación del 30% de las capacidades de velocidad y aceleración. Además, el algoritmo es capaz de asegurar una autonomía final con un 1,25% de error en presencia de ruido de sensor y actuador.The Eco-Driving profiles are algorithms capable to use additional information in order to create recommendations or limitation over the driver capabilities. They increase the autonomy of the vehicle but currently its usage is not related to the autonomy required by the driver. For this reason, in this paper, the Eco-Driving challenge is translated into two layers optimal controller designed for pure electric vehicles. This controller is oriented to ensure that the energy available is enough to complete a demanded trip, adding speed limits to control the energy consumption rate. The mechanical and electrical models required are exposed and analyzed. The cost function is optimized to correspond to the needs of each trip according to driver behavior, vehicle and trajectory information. The optimal controller proposed in this paper is a nonlinear model predictive controller (NMPC) associated to a nonlinear unidimensional optimization. The combination of both algorithms lets to increase around 50% the autonomy with a limitation of the 30% of the speed and acceleration capabilities. Also, the algorithm is capable to ensure a final autonomy with a 1.25% of error in the presence of sensor and actuator noise.Doctor en IngenieríaDoctorad

Dual Loop Rider Control of a Dynamic Motorcycle Riding Simulator

Compared to the automotive industry, the use of simulators in the motorcycle domain is negligible as for their lack of usability and accessibility. According to the state-of-the-art, it is e.g. not possible for motorcyclists to intuitively control a high-fidelity dynamic motorcycle riding simulator when getting in contact with it for the first time. There are four main reasons for the insufficient simulation quality of dynamic motorcycle riding simulators: ▪ The instability of single-track vehicles at low speed, ▪ The steering force-feedback with highly velocity-dependent behavior, ▪ Motion-simulation (high dynamics, roll angle, direct contact to the environment), ▪ The specific influence of the rider to vehicle dynamics (incl. rider motion). The last bullet point is peculiar for motorcycles and dynamic motorcycle riding simulators in comparison with other vehicle simulators, as motorcycles are significantly affected in their dynamics by the rider’s body motion. However, up until today, almost no special emphasis has been put on the consideration of rider motion on dynamic motorcycle riding simulators. In this thesis, a motorcycle riding simulator is designed, constructed and put into operation. The focus here is attaching a real rider to a virtual motorcycle. Based on a commercially available multi-body-simulation model, a simulator architecture is designed, that allows to control the virtual motorcycle not only by steering, but by rider leaning as well. This is realized by determining the so-called rider induced roll torque, that allows a holistic measurement of the apparent coupling forces between rider and simulator mockup. Performance measures and study concepts are developed that allow to rate the system. In expert and participant studies, the influence of the system on the riding behavior of the simulator is investigated. It is shown that the rider motion determination allows realistic control inputs and has a positive effect on the stabilization at various velocities. The feedback of the rider induced roll torque to the virtual dynamics model allows study participants to control the virtual motorcycle more intuitively. The vehicle states during cornering are affected as expected from real riding. First results indicate that it becomes easier for naïve study participants to access the simulator in first-contact scenarios. The achieved improvements regarding the rideability of the simulator however do not suffice to overcome the abovementioned challenges to a degree that allows for a completely intuitive interaction with the simulator throughout the whole dynamic range

Brake Steer Torque Optimized Corner Braking of Motorcycles

This thesis deals with the Brake Steer Torque (BST) induced stand-up tendency of Powered Two Wheelers (PTW) and measures to lower the associated risk for running wide on curve accidents with sudden, unforeseen braking. Focus is set on the BST Avoidance Mechanism (BSTAM), a chassis design that eliminates the BST through lateral inclination of the kinematic steering axis. A simple mathematical model is used to identify its main influences on the driving behavior and derive an optimized system layout. Its theoretical potential is evaluated against the standard chassis using different cornering adaptive brake force distributions and riding styles. For the first time ever, a motorcycle with state-of-the-art brake system (Honda CBR 600 RR, C-ABS) is equipped with a BSTAM and tested in corner braking experiments. Compared to the baseline, it is significantly reducing BST related disturbances and improving directional control. The gained insights can be stepping stones to enhance PTW safety by enabling future assistance systems with autonomous corner braking

Advances in Intelligent Vehicle Control

This book is a printed edition of the Special Issue Advances in Intelligent Vehicle Control that was published in the journal Sensors. It presents a collection of eleven papers that covers a range of topics, such as the development of intelligent control algorithms for active safety systems, smart sensors, and intelligent and efficient driving. The contributions presented in these papers can serve as useful tools for researchers who are interested in new vehicle technology and in the improvement of vehicle control systems

Optimal handling characteristics for electric vehicles with torque vectoring.

Torque vectoring by virtue of independent electric motors is the focus of an increasing number of studies as electric vehicles gain prominence as the chosen direction for the automotive industry. Building on active yaw control systems developed over the past decades, torque vectoring benefits from the high-responsiveness and controllability of the electric motor actuator. Furthermore, and especially in the case of vehicles equipped with one independent motor per wheel, the overall performance envelope of the vehicle is significantly improved, as well as the ability to actively shape the vehicle handling. Much attention has been focussed on controller development and control allocation aspects of torque vectoring controllers, but little on the appropriate yaw rate reference. Optimal control studies have been successfully used to mimic the expert driver in both minimum-time circuit racing and high-sideslip rally driving, and can offer insight into how to optimally tune active chassis control systems, such as torque vectoring yaw control. The main aim of this thesis was to investigate the optimal handling characteristics of an electric vehicle with four independent electric motors at the limits of performance. A TV controller was first developed for a prototype sportscar with 4 independent motors, employing a model-based design process that encompassed real-time software in the loop testing. Real-world track testing demonstrated the controller was able to successfully modify the handling characteristic of the vehicle in both understeer and oversteer directions, achieving good controller performance in steady-state and transient manoeuvres. The limit performance of the TV-controlled vehicle was subsequently investigated in the simulation domain. Numerical techniques were used to solve optimal control problems for a single-track vehicle model with linear tyres and an external yaw moment term representing the overall yaw moment arising from the difference in torques at each wheel. For a U-turn manoeuvre, it was shown that torque vectoring significantly lowers manoeuvre time in comparison with the vehicle without TV active, and that modifying the passive understeer gradient does not affect manoeuvre time. The system dynamics were reformulated to include a feedback torque vectoring controller. The target yaw rate reference was varied and it was found that the manoeuvre time was highly sensitive to the yaw rate reference. For minimising laptime, the target understeer gradient should be set to the passive understeer gradient value. The methodology was repeated for a higher fidelity model including nonlinear tyres and lateral load transfer, and found that when the torque vectoring controller was included in the system dynamics, the manoeuvre time showed little sensitivity to the target understeer gradient. Following the contradictory results of the optimal control problems, the vehicle models were investigated next. Time optimal yaw rate gain surfaces were generated from further minimum-time optimal control problems. Open-loop manoeuvres investigating effects of tyre model, lateral load transfer and torque vectoring generation mechanism found that tyre modelling was the dominant differentiator and tyre nonlinearity is an essential modelling consideration. Optimal control techniques have been used for high sideslip manoeuvring for conventional vehicles but no studies have explored the effects of torque vectoring on agility. In the final chapter, an aggressive turn-around manoeuvre was simulated and it was found that torque vectoring can significantly increase agility and reduce the space taken for an aggressive turn-around manoeuvre. Reducing yaw inertia increased agility, as well as increasing longitudinal slips limits. A critique of agility metrics in this context was given.PhD in Transport System

An Experimental Investigation of Human/Bicycle Dynamics and Rider Skill in Children and Adults.

While humans have been riding bicycles for nearly 200 years, the dynamics of how exactly they achieve this are not well understood. The overall goals of this dissertation were to identify the major control strategies that humans use to balance and steer bicycles, as well as to identify performance metrics that reliably distinguish rider skill level. To achieve these goals, we introduced: a) a novel instrumented bicycle to measure rider control inputs and bicycle response outputs, b) an experimental design and analytical approach for tracking and quantifying rider learning, and c) an experimental design and analytical approaches to measure the dynamics of human/bicycle balance and quantify rider balance performance. We employed variations of the instrumented bicycle in three studies that focused on: 1) how adult riders control bicycle kinematics during steady-state turning, 2) the initial learning of steering and balance control as children learn to ride bicycles, and 3) the balance skill of adult expert and novice riders. The findings from these studies advance our understanding of the types of control used by human riders, and simultaneously, quantify rider learning and skill. During steady-state turning, rider lean strongly influences steering torque, suggesting that rider lean plays an important role in bicycle control. Children learned to ride after successfully learning how to steer in the direction of bicycle roll, thereby increasing the correlation between steer and bicycle roll angular velocities (coefficient of determination increased from 0.22 to 0.75 during the learning process). In adults, the superior balance performance of skilled versus novice riders is revealed by highly correlated lateral positions of the center of pressure and center of mass (coefficients of determination of 0.97 versus 0.89, respectively). In achieving their superior balance performance, skilled riders employed more rider lean control, less steer control, and used less control effort than novice riders. We conclude that rider lean (i.e., any lateral movements of the rider) plays a dominant role in both steering and balancing a bicycle, and that achieving balance requires coordinating both steer and rider lean (the two rider control inputs) with bicycle roll (the bicycle response).PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98003/1/smcain_1.pd