A Multibody Model for the Simulation of Bicycle Suspension Systems

The paper describes a two-dimensional mathematical model for the motion of a bicycle-rider system with wheel suspensions. It focusses on the prediction of vibrational stress on the rider due to uneven track. The model was evaluated by comparing its predictions with measuring data concerning weighted accelerations on the human body, depending on various bicycle designs and road surfaces. For the intended purpose the predictions for vibrational stress and vibrational behaviour are sufficiently precise, and the model turns out to be adequate for designing and developing bicycle suspensions.     

Large motion mountain biking dynamics

A bond graph model of a mountain bike and rider is created to develop baseline predictions for the performance of mountain bikes during large excursion maneuvers such as drops, jumps, crashes and rough terrain riding. The model assumes planar dynamics, a hard-tail (front suspension only) bicycle and a rider fixed to the bicycle. An algorithm is developed to allow tracking of a virtual tire-ground contact point for events that separate the wheels from the ground. This model would be most applicable to novice mountain bikers who maintain a nearly rigid relationship between their body and the bicycle as opposed to experienced riders who are versed in controlling the bicycle independent of the body. Simulations of a steep drop are performed for various initial conditions to qualitatively validate the predictions of the model. Results from this model are to be compared to experimental data and more complex models in later research, particularly models including a separate rider. The overarching goals of the research are to examine and understand the dynamics and control of interactions between a cyclist and mountain bike. Specific goals are to understand the improvement in performance afforded by an experienced rider, to hypothesize human control algorithms that allow riders to perform manoeuvres well and safely, to predict structural bike and body forces from these maneuvers and to quantify performance differences between hard-tail and full suspension bicycles.     

Large motion mountain biking dynamics

A bond graph model of a mountain bike and rider is created to develop baseline predictions for the performance of mountain bikes during large excursion maneuvers such as drops, jumps, crashes and rough terrain riding. The model assumes planar dynamics, a hard-tail (front suspension only) bicycle and a rider fixed to the bicycle. An algorithm is developed to allow tracking of a virtual tire-ground contact point for events that separate the wheels from the ground. This model would be most applicable to novice mountain bikers who maintain a nearly rigid relationship between their body and the bicycle as opposed to experienced riders who are versed in controlling the bicycle independent of the body. Simulations of a steep drop are performed for various initial conditions to qualitatively validate the predictions of the model. Results from this model are to be compared to experimental data and more complex models in later research, particularly models including a separate rider. The overarching goals of the research are to examine and understand the dynamics and control of interactions between a cyclist and mountain bike. Specific goals are to understand the improvement in performance afforded by an experienced rider, to hypothesize human control algorithms that allow riders to perform manoeuvres well and safely, to predict structural bike and body forces from these maneuvers and to quantify performance differences between hard-tail and full suspension bicycles.     

A Model for Determining Rider Induced Energy Losses in Bicycle Suspension Systems

The energy dissipated by the suspension systems used for off-road bicycles is a major concern due to the limited power source in cycling. Rider induced energy losses are those that arise from the muscular action of the rider. The purpose of this study was to develop and verify a dynamic model of a seated cyclist riding an off-road bicycle up a smooth road. With the absence of terrain irregularities, all suspension motion was rider induced. Knowing the stiffness and dissipative characteristics of the suspension elements, the power dissipated by the suspensions was calculated.

Simulation results were compared to suspension deflections that were experimentally measured for a cyclist riding a commercially available dual suspension bicycle up a 6% grade at 6.5m/s. For this particular case, no fork motion was observed in the experiments which was consistent with the simulation results. For the rear suspension, the mean and amplitude of the largest harmonic were experimentally determined to be 6.6 and ±2.7 mm respectively. Simulation results were within 0.7mm of the mean and within 0.3mm of the amplitude. The only major discrepancy between the experiments and the simulations was the presence of a phase lag in the simulation results which was attributed to inter-subject variability. The power dissipated by the rear suspension was calculated to be 6.9 Watts or 1.3% of the total power input by the rider. Given the grade and forward velocity, this translated into an equivalent mass of 1.8 kg. Thus, the bicycle appeared to be roughly 12% heavier than it actually was.     

A tube-based robust nonlinear predictive control approach to semiautonomous ground vehicles

This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents a systematic way of enforcing robustness during the MPC design stage. A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre line. A force-input nonlinear bicycle vehicle model is developed and used in the RNMPC control design. A robust invariant set is used in the RNMPC design to guarantee that state and input constraints are satisfied in the presence of disturbances and model error. Simulations and experiments on a vehicle show the effectiveness of the proposed framework.     

Control Behaviour of Motorcycle Riders

The control behaviour of motorcycle riders is studied by means of a simulation model for the ridermotorcycle system, which stresses the control actions of the riders. The rider model describes the major steering torque control as well as the rider's own body control actions. This simulation model is applied to a single lane change maneuver and the results of this simulation are compared with the experiments in order to examine its validity.     

Model predictive driving simulator motion cueing algorithm with actuator-based constraints

The simulator motion cueing problem has been considered extensively in the literature; approaches based on linear filtering and optimal control have been presented and shown to perform reasonably well. More recently, model predictive control (MPC) has been considered as a variant of the optimal control approach; MPC is perhaps an obvious candidate for motion cueing due to its ability to deal with constraints, in this case the platform workspace boundary. This paper presents an MPC-based cueing algorithm that, unlike other algorithms, uses the actuator positions and velocities as the constraints. The result is a cueing algorithm that can make better use of the platform workspace whilst ensuring that its bounds are never exceeded. The algorithm is shown to perform well against the classical cueing algorithm and an algorithm previously proposed by the authors, both in simulation and in tests with human drivers.     

Control effects of steer-by-wire system for motorcycles on lane-keeping performance

This study discusses the control effects of the steer-by-wire (SBW) system for motorcycles on the lane-keeping performance by examining computer simulation with a rider-vehicle system which consists of a simplified vehicle model, a rider control model and the controller of the SBW system. The SBW system, which compensates the rolling angle deviation between the desired rolling angle intended by the rider and the actual rolling angle, improves the lane-keeping performance of the rider-vehicle system under the steering torque disturbance. The SBW system is, on the other hand, not effective in the lane-keeping performance under the lateral force disturbance. In addition, the lane-keeping assistance (LKA) system is applied to the SBW system and the cooperativeness of the SBW and the LKA systems is examined. The LKA system improves the lane-keeping performance of the SBW system under not only the steering torque disturbance but also the lateral force disturbance.     

基于模型预测控制的智能车轨迹跟踪控制研究

为了完成智能车的轨迹跟踪,提出一种基于模型预测控制的轨迹跟踪方法,利用将运动学模型这个非线性系统线性化的方案,来获得必须的线性时变系统,采取模型预测控制的三要素来设计控制器。并且基于MPC在控制过程中能增加多种约束的优点,建立基于车辆运动学模型的约束做轨迹跟踪仿真实验,最后,基于山东理工大学智能车平台上GPS提供的定位信息,在校园中采集路线并对前提规划好的的轨迹进行实车验证。实验结果表明:基于MPC算法所设计的控制器能快速且稳定地跟踪期望轨迹。     

旅游型城市公共自行车道路交通设计方法

该文以西安明城墙旅游功能区公共自行车项目为依托,以骑行者为设计尺度,首先,总结了PBS系统的发展模式,包括企业自主发展、政府主导发展和政企合作发展;其次,基于TransCAD宏观交通仿真和"哥尼斯堡七桥"理论,提出公共自行车道路线规划及优化方法;然后,通过原材料、试验路检测、抗污染和耐久性破坏试验分析,提出彩色路面工程设计方案;最后,在自行车交通特性分析基础上,提出公共自行车道路横断面和交叉口交通安全设计方法。     

基于模型预测控制的半挂汽车主动防侧倾控制方法

提出了一种半挂汽车主动防侧倾控制方法。搭建了一个七自由度动力学模型和一个三自由度参考模型;用无迹Kalman滤波的方法,来估计车辆的横向载荷转移率;确定优化目标,运用模型预测控制(MPC)理论进行最优化求解,得到各车轴的主动防侧倾力矩;在Simulink/Trucksim联合仿真环境中,进行仿真对比与分析。结果表明:在本文的MPC控制器和PID控制器作用下,半挂汽车各状态量皆收敛,且横向载荷转移率保持在0.7以内;相比于PID控制,MPC控制所需的防侧倾力矩更小更均衡,各状态量变化也更加平稳。因此,本MPC控制器在提升半挂汽车侧倾稳定性的同时具有较好的鲁棒性。     

Optimal control to modelling motorcycle rider steering: local versus global coordinate systems in rider preview

The response of a motorcycle is heavily dependent on the rider’s control actions, and consequently a means of replicating the rider’s behaviour provides an important extension to motorcycle dynamics. The primary objective here is to develop effective path-following simulations and to understand how riders control motorcycles. Optimal control theory is applied to the tracking of roadway by a motorcycle, using a non-linear motorcycle model operating in free control by steering torque input. A path-following controller with road preview is designed by minimising tracking errors and control effort. Tight controls with high weightings on performance and loose controls with high weightings on control power are defined. Special attention is paid to the modelling of multipoint preview in local and global coordinate systems. The controller model is simulated over a standard single lane-change manoeuvre. It is argued that the local coordinates point of view is more representative of the way that a human rider operates and interprets information. The simulations suggest that for accurate path following, using optimal control, the problem must be solved by the local coordinates approach in order to achieve accurate results with short preview horizons. Furthermore, some weaknesses of the optimal control approach are highlighted here.     

A nonlinear virtual rider for motorcycles

This work presents a virtual rider for the guidance of a nonlinear motorcycle model. The target motion is defined in terms of roll angle and speed. The virtual rider inputs are the steering torque, the rear-wheel driving/braking torque and front-wheel braking torque. The virtual rider capability is assessed by guiding the nonlinear motorcycle model in demanding manoeuvres with roll angles of 50° and longitudinal accelerations up to 0.8 g. Considerations on the effective preview distance used by the virtual rider are included.     

A review on motorcycle and rider modelling for steering control

The paper is a review of the state of knowledge and understanding of steering control in motorcycles and of the existing rider models. Motorcycles are well known to have specific instability characteristics, which can detrimentally affect the rider's control, and as such a suitable review of these characteristics is covered in the first instance. Next, early models which mostly treat riding as a regulatory task are considered. A rider applies control based on sensory information available to him/her, predominantly from visual perception of a target path. The review therefore extends to cover also the knowledge and research findings into aspects of road preview control. Here, some more emphasis is placed on recent applications of optimal control and model predictive control to the riding task and the motorcycle–rider interaction. The review concludes with some open questions which naturally present a scope for further study.     

基于改进粒子群优化算法的多目标自适应巡航控制

跟驰过程中,在保证安全性的前提下为了提升自适应巡航控制(ACC)系统的舒适性和燃油经济性,研究了多目标自适应巡航控制算法.在建立车间纵向运动学模型的基础上,根据模型预测控制理论,设计综合考虑安全性、舒适性、燃油经济性以及车辆自身限制等因素的目标函数和约束条件,并引入松弛因子向量软化硬约束边界解决无可行解问题.进一步在滚...     

基于MPC的液压混合动力车辆能量管理策略研究

针对双轴并联式液压混合动力车辆(PHHV),以蓄能器荷电状态(SOC)和发动机瞬时燃油质量流量m8f为输入量,发动机需求功率比例φ为输出量,以油耗最小为目标函数设计了模型预测控制器(MPC)进行PHHV的能量管理。基于MATLAB/Simulink平台搭建了包括需求功率计算、发动机、蓄能器和泵/马达等主要部件的PHHV车辆模型并进行MPC能量管理。研究结果表明,在美国道路城市循环工况(UDDS)下,MPC管理下的PHHV能充分发挥混合动力的特点,合理调节分配发动机和液压单元的需求功率,降低行驶过程的总油耗。     

On the wobble mode of a bicycle

Wheel shimmy and wobble are well-known dynamic phenomena at automobiles, aeroplanes and motorcycles. In particular, wobble at the motorcycle is an (unstable) eigenmode with oscillations of the wheel about the steering axis, and it is no surprise that unstable bicycle wobble is perceived unpleasant or may be dangerous, if not controlled by the rider in time. Basic research on wobble at motorcycles within the last decades has revealed a better understanding of the sudden onset of wobble, and the complex relations between parameters affecting wobble have been identified. These fundamental findings have been transferred to bicycles. As mass distribution and inertial properties, rider influence and lateral compliances of tyre and frame differ at bicycle and motorcycle, models to represent wobble at motorcycles have to prove themselves, when applied to bicycles. For that purpose numerical results are compared with measurements from test runs, and parametric influences on the stability of the wobble mode at bicycles have been evolved. All numerical analysis and measurements are based on a specific test bicycle equipped with steering angle sensor, wheel-speed sensor, global positioning system (GPS) 3-axis accelerometer, and 3-axis angular velocity gyroscopic sensor.     

基于TTCAN的燃料电池发动机分布式控制系统硬件在环仿真平台

建立了满足硬件在环仿真测试要求的燃料电池发动机模型及基于TTCAN网络通信的分布式控制系统模型;定量分析了TTCAN的循环周期和信号延迟之间的关系;基于MPC555设计了电气系统子节点软件,并对该节点进行了硬件在环仿真测试,验证了硬件在环仿真平台的有效性。     

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.     

Development of an experimental methodology to evaluate the influence of a bamboo frame on the bicycle ride comfort

In the current environment of increased emphasis on sustainable transport, there is manifold increase in the use of bicycles for urban transport. One concern which might restrict the use is the ride comfort and fatigue. There has been limited research in addressing the difficulty in bicycle ride comfort quantification. The current study aims to develop a methodology to quantify bicycle discomfort so that performance of bicycles constructed from bamboo and aluminium alloy can be compared. Experimentally obtained frequency response functions are used to establish a relation between the road input and the seat and rider response. A bicycle track input profile based on standard road profiles is created so as to estimate the acceleration responses. The whole-body-vibration frequency weighting is applied to quantify the perception of vibration intensity so that eventual discomfort ranking can be obtained. The measured frequency response functions provide an insight into the effect of frame dynamics on the overall resonant behaviour of the bicycles. The beneficial effect of frame compliance and damping on lower modes of vibration is very clear in the case of bamboo frame, in turn affecting seat and rider response. In the bamboo frame, because of multiple resonances, the frequency response of the handlebar is smaller at higher frequencies suggesting effective isolation. Further improvements may have come from the joints made from natural composites. Overall, based on the comparative analysis and the methodology developed, bamboo frame shows significant improvement in ride comfort performance compared with the aluminium frame.