Electric Motorbike Research Articles

A Numerical Thermal Analysis of a Battery Pack in an Electric Motorbike Application

Today, electric driven motorbikes (e-motorbikes) are facing multiple safety, functionality and operating challenges, particularly in hot climatic conditions. One of them is the increasing demand for efficient battery cooling to avoid the potential thermal stability concerns due to extreme temperatures and the conventional plastic enclosure of the battery pack. A reliable and efficient thermal design can be formulated by accommodating the battery within an appropriate battery housing supported by a cooling configuration. The proposed design includes a battery pack housing made of high conductive materials, such as copper (Cu) and aluminum (Al), with an adequate liquid cooling system. This study first proposes a potted cooling structure for the e-motorbike battery and numerical studies are carried out for a 72 V, 42 Ah battery pack for different ambient temperatures, casing materials, discharge rates, coolant types, and coolant temperatures. Results reveal that up to 53 °C is achievable with only the Cu battery housing material. Further temperature reduction is possible with the help of a liquid cooling system, and in this case, with the use of coolant temperature of 20 °C, the battery temperature can be maintained within 28 °C. The analysis also suggests that the proposed cooling system can keep a safe battery temperature up to a 5C rate. The design was also validated for different accelerated driving scenarios. The proposed conceptual design could be exploited in future e-motorbike battery cooling for optimum thermal stability.

Sound Visualization and Convolutional Neural Network in Fault Diagnosis of Electric Motorbike

This study proposed convolutional neural network (CNN) training for different figure recognition to diagnose electric motorbike faults. Traditional motorbike maintenance is usually carried out by technicians to find the problem step by step. Many resources are wasted and time consumed in diagnosing maintenance problems. Due to rising environmental protection awareness, motorbike power systems gradually transformed from combustion engines into the electric motor. The sound amplitude generated by the combustion engine is great and may cover other faulty sounds. The electric power system sound amplitude is greatly decreased, permitting various fault diagnosis to be performed by extracting the electric motor sound. With the development of computers and image processing, deep learning neural network for picture recognition technology becomes more feasible. This study presents the motor system sound visualization for fault diagnosis. First obtain the sound signals of the motor in the five different states of the operation in the laboratory and the road test, and draw the time domain graph, frequency domain graph and spectrogram graph to be used as the test database. The results graphs of various states were trained through a CNN. The signal states were then classified to achieve fault diagnosis. Experiments and identification results show that the spectrogram and CNN method can identify motorbike faults most effectively compared to the time domain graph and the frequency domain graph.

Fully self-powered instantaneous wireless traffic monitoring system based on triboelectric nanogenerator and magnetic resonance coupling

The self-powered wireless sensor systems are highly sought for the information era, as they are able to link everything together, yet without the need for electric power supply. They have been exploited for applications in various fields, particularly for environment-related ones. Here, we propose a fully self-powered triboelectric nanogenerator (TENG)-based wireless traffic monitoring system for real-time monitoring of illegally entered electric motorbikes on the footpaths, and flow rates of pedestrians and motorbikes, and speed and driving direction of electric motorbikes on non-motorized lanes. The TENG was used to directly convert the energy from pedestrian’s stepping and electric motorbike’s rolling into an oscillating signal with encoded sensing information, and transmit it to the receiver wirelessly via magnetic resonance coupling. Results showed that the multi-variable traffic monitoring system can identify pedestrians and motorbikes, check the illegally entered motorbikes on the footpath, and measure speed of the motorbikes with an accuracy of over 94%, monitor driving direction of electric motorbikes on non-motorized lanes. The self-powered wireless traffic monitoring system is simple in structure, low cost, easy to install, and spontaneous response to the traffic condition, and does not contain electronic devices, microcontrollers and transmission chips but the passive components, hence it has great application potential as a green intelligent traffic monitoring system. The self-powered wireless traffic monitoring system based on TENG, which can monitor real-time electric motorbikes illegally entering in the footpaths, and flow rates of pedestrians and motorbikes, and speed measurement, driving direction of electric motorbikes on non-motorized lanes. • A triboelectric nanogenerator (TENG) based self-powered instantaneous wireless traffic monitoring system is developed which yet does not contain electronic devices, but the passive components. • The traffic recognition monitoring system can identify pedestrians on the sidewalk and illegal vehicles entering the footpath. • The traffic speed monitoring system can realize the function of electric vehicle speed measurement and driving direction judgment.

Optimal charging of an electric vehicle battery pack: A real-time sensitivity-based model predictive control approach

Lithium-ion battery packs are usually composed of hundreds of cells arranged in series and parallel connections. The proper functioning of these complex devices requires suitable Battery Management Systems (BMSs). Advanced BMSs rely on mathematical models to assure safety and high performance. While many approaches have been proposed for the management of single cells, the control of multiple cells has been less investigated and usually relies on simplified models such as equivalent circuit models. This paper addresses the management of a battery pack in which each cell is explicitly modelled as the Single Particle Model with electrolyte and thermal dynamics. A nonlinear Model Predictive Control (MPC) is presented for optimally charging the battery pack while taking voltage and temperature limits on each cell into account. Since the computational cost of nonlinear MPC grows significantly with the complexity of the underlying model, a sensitivity-based MPC (sMPC) is proposed, in which the model adopted is obtained by linearizing the dynamics along a nominal trajectory that is updated over time. The resulting sMPC optimizations are quadratic programs which can be solved in real-time even for large battery packs (e.g. fully electric motorbike with 156 cells) while achieving the same performance of the nonlinear MPC.

SOLUTION FOR SAVING ENERGY AND REDUCING ENVIRONMENTAL POLLUTION ON MOTORCYCLES

This report aims to introduce a solution for saving fuel and reducing environmental pollution on motorcycles in order to increase the operational capacity of a very popular means of transport in Vietnam today. In this solution, we use an electric motorbike which is combined with a heat engine to meet the requirements of increasing vehicle performance. The article presents the methods to design, to install the parts of the system and the heat engine on electric motorbike as well as experiment and evaluate the effectiveness of the solution

Mitigating Greenhouse Gas Emissions from Passenger Transport Sector in Megacities: A case of Ho Chi Minh City

This research aims to propose mitigation measures to reduce the greenhouse gas emissions from passenger transport sector for Ho Chi Minh City, Vietnam. The Extended Snapshot tool is used to calculate the socio-economic development indicators and transport demand for base year 2013, and then estimate the transport demand based on the socio-economic development in target year 2030. In the base year 2013, the air pollutants (NO2, CO, PM10, Pb, etc.) are monitored at the six main stations to analyse the air pollution situation due to transportation activities. In the target year 2030, two scenarios are developed with the same socio-economic development and transport demand projections. Business-as-usual scenario does not consider the mitigation measures to reduce the greenhouse gas emissions while the countermeasure scenario does. Among the 940.5 kt CO2-eq reduction (15.0 % of emissions from passenger transport in 2030’s business-as-usual scenario), the promotion of energy-efficient vehicles helps to reduce 631.0 kt CO2-eq, followed by 146.7 kt CO2-eq reduction by modal shift from motorbike to mass rapid transports. The shift from fuel-motorbike to electric motorbike helps to reduce 83.2 kt CO2-eq, together with 41.4 kt CO2-eq reduction by shifting from conventional bus to compressed natural gas bus. The promotion of eco-driving with digital tachograph in passenger car helps to reduce 38.2 kt CO2-eq. As the co-benefit, the air pollution due to transportation activities might be reduced thanks to the implementation of mitigation measures to reduce the greenhouse gas emissions.

Brushless DC Motor Speed Controller for Electric Motorbike

<p>This paper presents a control scheme for speed control system in brushless dc (BLDC) motor to be utilized for electric motorbike. While conventional motorbikes require engine and fuel, electric motorbikes require DC motor and battery pack in order to be powered up. The limitation with battery pack is that it will need to be recharged after a certain period and distance. As the recharging process is time consuming, a PID controller is designed to maintain the speed of the motor at its optimum state, thus ensuring a longer lasting battery time (until the next charge). The controller is designed to track variations of speed references and stabilizes the output speed accordingly. The simulation results conducted in MATLAB/SIMULINK® shows that the motor, equipped with the PID controller was able to track the reference speed in 7.8x10<sup>-2</sup> milliseconds with no overshoot. The result shows optimistic possibility that the proposed controller can be used to maintain the speed of the motor at its optimum speed.</p>

Road Transportation Energy Demand and Environmental Emission: A Case of Kathmandu Valley

The current trade embargo imposed by India has created an acute fuel crisis in Nepal which has stranded more than 50% of public vehicles affecting the supply of all the necessities and daily life of people. This study has shown some alternative ways to manage the vehicle fuel demand especially for urban transportation in the Kathmandu valley, Nepal. The modeling tool, Long-range Energy Alternative Planning System (LEAPS) has been used to develop a bottom-up model to estimate the energy demand and environmental emissions in the Kathmandu valley for the period 2016-2030 AD. Besides the Reference scenario, four alternative scenarios (Public Bus Penetration, Improved Fuel Economy, Electric Motorbike and Hybrid Electric Car) have been developed. In the Reference scenario, the cumulative energy demand will reach 142,092 thousand GJ within the analysis period. About 65% of this demand comes from motorbikes and light duty vehicles. If all of the alternative scenarios are implemented together, about 38% of energy demand and 54% of CO2 emission can be avoided compared to the reference scenario within the study period. About 1641 million US$ at the current market price can be avoided within the analysis period if all of these four options are applied together.HYDRO Nepal: Journal of Water Energy and EnvironmentVolume 18, 2016, JanuaryPage 30-40

The development of an exchangeable PEMFC power module for electric vehicles

This paper develops an exchangeable fuel-cell power module that is replaceable on different light electric vehicles (LEVs). The module consists of a proton exchange membrane fuel-cell (PEMFC) and two battery sets, which provide continuous power for LEVs. The study includes three topics: fuel-cell control, power management, and system modularization and vehicle integration. First, we design robust controllers for the PEMFC to provide a steady voltage or current for charging the battery sets. Second, we develop a serial power train that can provide continuous power for driving the vehicle motors. Third, we modularize a power system that can be easily implemented on different LEVs. We build the system on Matlab™ SimPowerSystem for simulation before road tests, and integrate the power module onto a mobility car and an electric motorbike for experimental verification. Based on the results, the proposed systems are deemed effective.

Integration of a Folding Electric Two-wheeler Vehicle for a Future Commuting Transportation

The paper issues the development, building and testing of a Folding Electric Motorbike, a lightweight, low cost and all-electric two-wheeler vehicle taking full advantage on today’s city infrastructure. The technology offers drivers to combine transportation methods, lowering cost, and greenhouse gas emission. The paper documents innovative studies on how the technology can be used to explode the today’s transportation system and be used to bridge the gap of today’s challenges and future solutions. The optimum components to be used in the small, lightweight vehicles are selected based on the technology’s functional requirements. The selection of motorbike’s drivetrain components is based on the latest available technology, with respect to economic viability. The technologies first two development stages are described. In the first development stage the vehicle’s functional requirements are defined. This is followed by a feasibility study and a realization on technologies capabilities. The feasibility study is performed by developing, building and evaluating an alpha-prototype vehicle. The research indicate that the possibility of developing a powerful , light-weight, low cost and all-electric two-wheeler vehicle taking full advantage on today’s city infrastructure is very prospective. The alpha-prototype was successfully constructed and is considered to be ready for further laboratory testing and test driving before continuations on a fully designed beta-prototype.

Abstracts

This paper develops an exchangeable fuel-cell power module that is replaceable on different light electric vehicles (LEVs). The module consists of a proton exchange membrane fuel-cell (PEMFC) and two battery sets, which provide continuous power for LEVs. The study includes three topics: fuel-cell control, power management, and system modularization and vehicle integration. First, we design robust controllers for the PEMFC to provide a steady voltage or current for charging the battery sets. Second, we develop a serial power train that can provide continuous power for driving the vehicle motors. Third, we modularize a power system that can be easily implemented on different LEVs. We build the system on Matlab™ SimPowerSystem for simulation before road tests, and integrate the power module onto a mobility car and an electric motorbike for experimental verification. Based on the results, the proposed systems are deemed effective.