All wheel drive electric motorcycle modelling and control.

Conventional motorcycles are powered through a chain or shaft linking the engine to the rear wheel. However, motorcycle riders are now facing riding conditions and obstacles where having only rear wheel drive can lead to vehicle damage, loss of control and an unstable front wheel during cornering and off-road riding in general. Traction and climbing ability are severely limited in extreme mountain conditions by only having the rear wheel to provide power. Accordingly, there is a need in the industry for a two-wheel drive motorcycle that efficiently and safely transfers power from the motor to the front wheel, because it provides the rider with increased ability to safely negotiate rough terrain. In this background, the design of an optimal torque distribution strategy implemented by two separate electric motors in an all-wheel-drive electric motorcycle has many potentialities not fully explored and deeply understood for two wheel vehicles, that makes this study interesting from a scientific point of view. With this in mind, the research project aims to design control systems for improving rider’s safety and vehicle performance at low as well as high speeds, especially in critical situations and rough terrains, taking into account the presence of the front wheel torque generated by a hub-mounted electric motor. At low speed the research investigates whether and how the front wheel torque helps the stabilization of the vehicle around the upright position, without any rider action required. The study is developed by deriving a simplified analytical model of the vehicle, which captures its lateral motion and a model-based control system, employing the sliding mode control technique. As further requirement, the motorcycle should be balanced in a small bounded area, by means of Multi Input control system. At medium and high speeds the study explores how and how much the traction torque repartition can improve continuously the vehicle performances in combined longitudinal and lateral acceleration situations, such as the exit of a curve, especially in those conditions where a traditional motorcycle falls down because it overcomes tyre adherence limits. Last purpose is achieved deriving a dynamical optimal traction strategy which does not require the a priori knowledge of the friction coefficient. Steady state analysis indicates outperformances of the all wheel drive motorcycle over the classical rear wheel drive one. Then, dynamical simulations of selected manoeuvres, in both flat and uneven road, corroborate the result

Robust stabilization of running self-sustaining two-wheeled vehicle

金沢大学理工研究域電子情報学系This paper deals with robust stabilization of running self-sustaining two-wheeled vehicle. Recently, some researches about stabilization of two-wheeled vehicle have been reported. These researches have achieved the stabilization running only by the steering control. However, an actual two-wheeled vehicle is running while accompanying stabilization by the rider. We have proposed the stabilization of two-wheeled vehicle in the state of stillness, and have shown the effectiveness. In this research, we compose the control system that aims at the running stabilization of two-wheeled vehicle. We use ℋ∞ mixed sensitivity problem to design the controller to achieve stability running even if the mass of two-wheeled vehicle changes. The experimental results show stability running even if the mass of two-wheeled vehicle changed. © 2007 IEEE

Path Following and Stabilization of an Autonomous Bicycle

In this thesis we investigate the problem of designing a control system for a modern bicycle so that the bicycle is stable and follows a path. We propose a multi-loop control architecture, where each loop is systematically designed using linear control techniques. The proposed strategy guarantees that the bicycle asymptotically converges to paths of constant curvature. A key advantage of our approach is that by using linear techniques analysis and controller design are relatively simple. We base our control design on the nonlinear (corrected) Whipple model, which has been previously verified for correctness and experimentally validated. The equations of motion for the nonlinear model are very complicated, and would take many pages to explicitly state. They also have no known closed form solution. To enable analysis of the model we linearize it about a trajectory such that the bicycle is upright and travelling straight ahead. This linearization allows us to arrive at a parameterized linear time-invariant state-space representation of the bicycle dynamics, suitable for analysis and control design. The inner-loop control consists of a forward-speed controller as well as a lean and steer controller. To keep the bicycle at a constant forward speed, we develop a high-bandwidth proportional controller that uses a torque along the axis of the rear wheel of the bicycle to keep the angular velocity of the rear wheel at a constant setpoint. To stabilize the bicycle at this forward speed, lean torque and steer torque are treated as the control signals. We design a state-feedback controller and augment integrators to the output feedback of the lean angle and steer angle to provide perfect steady-state tracking. To arrive at the gains for state feedback, linear-quadratic regulator methods are used. When following a constant-curvature path, a vehicle has a constant yaw rate. Using this knowledge, we begin designing the outer-loop path-following control by finding a map that converts a yaw rate into appropriate lean angle and steer angle references for the inner loop. After the map is completed, system identification is performed by applying a yaw-rate reference to the map and analyzing the response of the bicycle. Using the linear approximation obtained, a classical feedback controller for yaw-rate tracking is designed. In addition to yaw-rate control, to track a path the yaw angle of the bicycle must match that of the path and the bicycle must physically be on the path. To analyze these conditions a linear approximation for the distance between the bicycle to the path is found, enabling construction of a linear approximation of the entire system. We then find that by passing the signal for the difference in yaw rate and the distance through separate controllers, summing their output, and subtracting from the reference yaw rate of the path, the bicycle converges to the path. After developing the general design procedure, the final part of the thesis shows a step by step design example and demonstrates the results of applying the proposed control architecture to the nonlinear bicycle model. We highlight some problems that can arise when the bicycle is started far from the path. To overcome these problems we develop the concept of a virtual path, which is a path that when followed returns the bicycle to the actual path. We also recognize that, in practice, typical paths do not have constant curvature, so we construct more practical paths by joining straight line segments and circular arc segments, representing a practical path similar to a path that would be encountered when biking through a series of rural roads. Finally, we finish the design example by demonstrating the performance of the control architecture on such a path. From these simulations we show that using the suggested controller design that the bicycle will converge to a constant curvature path. Additionally with using the controllers we develop that in the absence of disturbance the bicycle will stay within the intended traffic lane when travelling on a typical rural road

A Linear Parameter-Varying Control Method for Inline Wheel Systems

The design of the bicycle and other single-track systems are continually evolving and have become a key tool for people and goods transportation worldwide [1],[2]. The form factor, carrying capacity, maneuverability, and cost of single-track vehicles makes them advantageous in a variety of circumstances and justifies their use case in the 21st Century [2] [3],[4]. As autonomous double track vehicles arrive on public roads, it is natural that single-track autonomous systems will be developed as well; however, the unstable and non-minimum phase dynamics of single-track vehicles make their control have an additional layer of complexity compared to double track vehicles. Although many researchers have provided commentary on the stability and tracking of a riderless bicycle, relatively few bodies of work have validated their analysis through experimental testing. This work successfully demonstrates that, through gain scheduling, a PID-type controller can balance a riderless single-track vehicle by using a linear actuator to implement front-fork steering control. This control system is novel in the way in which the front fork is actuated. The manual PID tuning process outlined in this body of work is also unique, as well as the specifics of the control law (although PID controllers have been used by other authors). The works of other authors on this topic is briefly summarized and a second-order dynamics system model is derived. Then controller analysis is simulated and then validated experimentally. Suggestions are also made on next steps that can be taken to build upon the work outlined in this thesis.MSEElectrical Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/169157/1/Ronald Smith Final Thesis.pd

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