The development of environmentally friendly road transport is now directly related to the introduction of electric actuators, high-voltage storage systems and the accumulation of electricity in transport. Thus, a significant variety of hybrid traction drive circuits appears, which can be charged from an external power source. However, all of them use hydrocarbon fuel for charging and storage of electricity, which emits CO2 while burning. Clean electric vehicles are the most efficient in terms of environmental indicators, since they use only electricity produced in power plants located far from the operation aureole of the electric vehicle, which allows to improve the environmental situation in megapolises significantly. As you know, energy complexes in different countries have different environmental efficiency and CO2 emissions during power generation are also present. Transition to the use of renewable energy sources, such as solar power plants, can give its effect, since at present, their productivity in the world reaches 400 GW, but the transmission of energy over distances reduces the efficiency. Thus, based on the development trends of solar power plants, it is important to consider the use of photovoltaic cells, the so-called “solar cells” directly on the electric vehicle itself in order to improve environmental friendliness.
Urban air pollution is clearly a constantly growing problem and the high level of urban air pollution has been shown to pose a significant risk to city dwellers. It is necessary to have low-cost sensors for data collection, ready data source allowing normal citizen to access to and gain information, and have prospect solutions (e.g. autonomous vehicle) for air pollution reduction in the city. The aim of the study is to illustrate the drivers behind the use of low-cost sensors and to review the performance of sensors. In addition, autonomous vehicle is expected to reduce pollution; therefore, the paper analyzes the benefits and adoption of autonomous vehicles in the future. The challenges and outlook for both low-cost sensor deployment and the adoption of self-driving vehicle will also be discussed. A literature review is used to obtain these aims. The study indicates that the main driver of low-cost sensor is to provide high-density spatiotemporal pollution data, assisting in creating emission inventories of pollutants and detecting pollution hotspots without capital investments. A number of performance aspects considered include the coefficients of determination (R2), variance (CV), repeatability, reproducibly and stability of the sensor. Self-driving vehicle is promising in the change of travel patterns and having impacts on the health of society. Technology and economic challenges, the willingness to use the sensor and the autonomous policy approach are the major challenges. In terms of the outlook, standard guidelines and the calibration methods for low-cost sensors, energy consumption savings and policy supporting for autonomous vehicle should be further investigated.
Electric bikes are a rising mode of transportation in developing countries as their use reduce the use of hydrocarbon-based energy sources as well as increases convenience for the commuters within the city by reducing traffic. Furthermore, the electric bikes have low noise emission and no exhaust gases produced, which improves the environmental footprint. Due to the Vietnam regulations, most electric bikes use brushless wheel-hub motors as the main drivetrain solution paired with various types of batteries. The key challenges in the design of the drivetrains are related to the efficiency and controllability areas, so the response of the drivetrain can be improved. The key area of improvement lies in the control system design to optimize the performance and energy consumption. This paper presents the research done on developing of optimization PID control algorithms by using GA (Generic Algorithm) and PSO (Particle Swarm Optimization) for driving a synchronized brushless DC motor for the electric bikes.
The article presents a process of designing the photovoltaic (PHV) converters system for an electric vehicle, shows the scheme of photovoltaic converters usage, the results of electric vehicle motion modeling with photovoltaic converters, and the results of road tests of an electric vehicle with an additional power source based on photovoltaic converters. The photovoltaic converters system and low-voltage system of an electric vehicle have a shared low-voltage battery, which allows the implementation of two schemes of electric vehicle power supply. Initially, the aggregate base was selected, then, taking into account the efficiency of each device included in the design of the new electric vehicle, mathematical modeling was carried out and showed good efficiency results of the photovoltaic converters system. Then, the prototype was manufactured and tested. The aggregate base included the battery of photovoltaic converters assembled in a certain way on the vehicle roof, the MPPT (maximum power point tracking) controller, the buffer storage device in the form of a 12 V battery, and the DC (direct current) converter that allows transmitting electricity from the buffer battery to the high-voltage system. Modeling of the electric vehicle motion considered typical operating modes, including energy costs for the operation of assistant systems of the electric vehicle, as well as including the consumption of low-voltage components. The tests were carried out according to the NEDC (New European Driving Cycle). As a result, implementation of photovoltaic converters with 21% efficiency allowed for the power reserve of the electric vehicle to be increased by up to 9%.
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