Abstract
Around the world, the e-bike has evolved from a recreational and sports object to an increasingly used means of transportation. Due to this, improving aspects such as range and energy efficiency has become very relevant. This article presents experimental models for the components’ efficiency of a mid-drive motor e-bike (charger; battery; and controller, motor, and reduction gears subsystem), and integrates them with previously elaborated models for the chain transmission system, thus generating an overall efficiency map of the e-bike. The range of the electric bicycle is analyzed by integrating the efficiency map of the system and its performance mathematical model, aiming to determine the per unit of distance battery energy consumption. The above-mentioned calculations are applied to develop a management strategy that can determine the optimal assistance level and chain transmission ratio, maximizing range and leaving speed unaffected. The driving strategy was compared against other driving techniques using computational analysis, this allowed for the observation of the proposed strategy improving the system’s range by reducing the battery energy consumption.
Highlights
This section initially presents the method by which the energy flow through the bicycle is analyzed, as well as the losses in its components; the equations for the system’s dynamic behavior and performance are presented; after that, the proposed driving strategy to increase the e-bike’s range is described; and a case study is showcased in which the performance of the driving strategy is compared with other driving techniques
This shows that, by using the assistance level (AL) and chain transmission ratio indicated by strategy one for each route, energy consumption was reduced by up to
This article presented a driving strategy focused on enhancing the range of mid-drive motor electric bicycles, based on the proper selection of the chain transmission ratio and the assistance level
Summary
Short ranges derived from the battery’s energy storage limitations bound their massification [5,6] For this reason, the performance modeling, the study of the components’ efficiency, and its integration play a fundamental role in improving range [7,8]. Stated the dynamic equations of an electric bicycle and performed physical tests with an electric bicycle equipped with sensors As a result, they described the operation of the system presenting the maximum power, speed, and instantaneous power against variations of weight, slope, and wind speed. Evtimov et al [10] performed experimental tests in different city routes with an electric bicycle equipped with sensors, enabling them to characterize aspects such as power, energy consumed, maximum current, maximum speed, regenerated Ah, and range.
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