This is a Masters Thesis completed at University College Dublin, Ireland in 2017 which involved augmenting an off-the-shelf electric bike with sensors to enable new services to be delivered to cyclists in cities. The application of primary interest was to control the cyclist's ventilation rate based on the concentration of local air pollutants. Detailed modelling and system design is presented for our Cyberphysical system which consisted of a modified BTwin e-bike, Cycle Analyst sensors, the cyclist themselves, a Bluetooth connected smartphone and our algorithms. Control algorithms to regulate the proportion of power the cyclist provided as a proxy for their ventilation rate were proposed and validated in a basic way, which were later proven significantly further in Further Work (see IEEE Transactions on Intelligent Transportation Systems paper: https://ieeexplore.ieee.org/abstract/document/8357977). The basic idea was to provide more electrical assistance to cyclists in areas of high air pollution to reduce the cyclist ventilation rate and thereby the amount of air pollutants inhaled. This presents an interesting control challenge due to the human-in-the-loop characteristics and the potential for impactful real life applications. A background literature review is provided on energy as it relates to cycling and some other applications are also discussed. A link to a video which demonstrates the system is provided, and also to a blog published by IBM Research about the system.
翻译:这是2017年在爱尔兰都柏林大学学院完成的一本《硕士论文》,内容包括增加一台配有传感器的现成电动自行车,以便能够向城市的骑自行车者提供新的服务。应用的主要兴趣是控制以当地空气污染物浓度为基础的骑自行车者的通风率。为我们的网络物理系统提供了详细的建模和系统设计,该系统包括一个经过修改的BTwin e-bike、循环分析器传感器、自行车分析器本身、一个连接蓝牙的智能手机和我们的算法。控制算法,以调节骑自行车者作为其通风率代用品提供的力量比例,这是以基本方式提出和验证的,后来在进一步的工作中大大证明了这一点(见IEEE关于智能运输系统的交易:https://ieexplore.ie.e.org/abstract/document 8357977)。 基本想法是向高空气污染地区的骑自行车者提供更多的电力援助,以减少自行车通风率,从而减少空气污染物的数量。这个控制算法是一个令人感兴趣的背景挑战,因为这个背景是人类-内循环系统的潜在应用。