scholarly journals IoT Based Control of Hybrid Energy Storage System for an Electric Vehicle using Super Capacitor and Battery

2021 ◽  
Vol 1979 (1) ◽  
pp. 012032
Author(s):  
K Balachander ◽  
A Amudha ◽  
M Mansoor Ali
2019 ◽  
Vol 8 (3) ◽  
pp. 3444-3448

As each day passes, we, humans, are attracted towards more and more technology for the easiness of our day to day life. One such technology, which has a very high scope in future and in the aspect of reducing pollution and providing clean environment, is the use of electric vehicles. Moreover, the electric vehicles provides long distance endurance and it is really minimizes the cost. This paper mainly discusses about the use and benefit of hybrid energy storage system for electric vehicle with the help of Neural Network Fitting Function technology, which is based on a controller. At last, comparison between graphs of a base model and the proposed model is also shown, which clearly shows reduction in variation of the battery current, super capacitor, load current and dc voltage graph.


Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2854 ◽  
Author(s):  
Danijel Pavković ◽  
Mihael Cipek ◽  
Zdenko Kljaić ◽  
Tomislav Mlinarić ◽  
Mario Hrgetić ◽  
...  

This contribution outlines the design of electric vehicle direct-current (DC) bus control system supplied by a battery/ultracapacitor hybrid energy storage system, and its coordination with the fully electrified vehicle driveline control system. The control strategy features an upper-level DC bus voltage feedback controller and a direct load compensator for stiff tracking of variable (speed-dependent) voltage target. The inner control level, comprising dedicated battery and ultracapacitor current controllers, is commanded by an intermediate-level control scheme which dynamically distributes the upper-level current command between the ultracapacitor and the battery energy storage systems. The feedback control system is designed and analytical expressions for feedback controller parameters are obtained by using the damping optimum criterion. The proposed methodology is verified by means of simulations and experimentally for different realistic operating regimes, including electric vehicle DC bus load step change, hybrid energy storage system charging/discharging, and electric vehicle driveline subject to New European Driving Cycle (NEDC), Urban Driving Dynamometer Schedule (UDDS), New York Certification Cycle (NYCC) and California Unified Cycle (LA92), as well as for abrupt acceleration/deceleration regimes.


Energy ◽  
2017 ◽  
Vol 140 ◽  
pp. 291-306 ◽  
Author(s):  
Jiageng Ruan ◽  
Paul David Walker ◽  
Nong Zhang ◽  
Jinglai Wu

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Cong Zhang ◽  
Haitao Min ◽  
Yuanbin Yu ◽  
Qingnian Wang ◽  
Huanli Sun

Although both battery and super-capacitor are important power sources for hybrid electric vehicles, there is no accurate configuration theory to match the above two kinds of power sources which have significantly different characteristics on energy and power storage for the goal of making good use of their individual features without size wasting. In this paper, a new performance is presented that is used for analysis and optimal design method of battery and super-capacitor for hybrid energy storage system of a parallel hybrid electrical vehicle. In order to achieve optimal design with less consumption, the power-energy function is applied to establish direct mathematical relationship between demand power and the performance. During matching process, firstly, three typical operating conditions are chosen as the basis of design; secondly, the energy and power capacity evaluation methods for the parameters of battery and super-capacitor in hybrid energy storage system are proposed; thirdly, the mass, volume, and cost of the system are optimized simultaneously by using power-energy function. As a result, there are significant advantages on mass, volume, and cost for the hybrid energy storage system with the matching method. Simulation results fit well with the results of analysis, which confirms that the optimized design can meet the demand of hybrid electric vehicle well.


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