Math Function Based Controller Applied to Electric/Hybrid Electric Vehicle

Math Function Based Controller Applied to Electric/Hybrid Electric Vehicle

Raghavaiah Katuri Srinivasa R. Gorantla 

Electrical and Electronics Engineering, Research Scholar, Vignan’s Foundation for Science, Technology and Research, Vadlamudi, Guntur, Andhra Pradesh 522213, India

Electrical and Electronics Engineering, Professor, Vadlamudi, Guntur, Andhra Pradesh 522213, India

Corresponding Author Email: 
rk_eeep@vignanuniversity.org
Page: 
15-21
|
DOI: 
https://doi.org/10.18280/mmc_a.910103
Received: 
3 January 2018
|
Accepted: 
13 April 2018
|
Published: 
31 March 2018
| Citation

OPEN ACCESS

Abstract: 

Hybrid Energy Storage System (HESS) has been implemented for better energy efficiency to Hybrid/Electric Vehicles (HEV/EV), in that the main source is battery and UltraCapacitor (UC) is the auxiliary source. Switching of the energy sources according to the electric vehicle speed also plays an important role, to improve the life of the battery. So designing of the controller is a dynamic factor in case of electric /hybrid electric vehicles. The main objective of this paper is to design a controller for the transition between the sources, battery and Ultracapacitor. Here controller has been designed based on the Math function coding and this can be termed as Math Function Based (MFB) Controller. The controller generates the signals to the converters based on the speed of the motor. The MFB controller mainly designed to work in four modes and for each and every mode separate math function has been created. The overall system has been simulated in MATLAB and plotted the all results with discussions.

Keywords: 

Electric Vehicles (EV), Hybrid Electric Vehicles(HEV), Converters, Battery, Ultracapacitor (UC), Hybrid Energy Storage System (HESS), Math Function Based (MFB) Controller.

1. Introduction
2. Proposed Model
3. Modes of Operation
4. Control Strategy Approach
5. Simulation Results and Discussions
6. Conclusion
  References

[1] Shen J, Khaligh A. (2016). Design and real-time controller implementation for a battery ultracapacitor hybrid energy storage system. IEEE Transactions on Industrial Informatics 12(5): 1910-8.

[2] Wu D, Todd R, Forsyth AJ. (2015). Adaptive rate-limit control for energy storage systems. IEEE Transactions on Industrial Electronics 62(7): 4231-40. 

[3] Xiang C, Wang Y, Hu S, Wang W. (2014). A new topology and control strategy for a hybrid battery-ultracapacitor energy storage system. Energies 7(5): 2874-96. 

[4] Cao J, Emadi A. (2012). A new battery/ultracapacitor hybrid energy storage system for electric, hybrid, and plug-in hybrid electric vehicles. IEEE Transactions on power electronics 27(1): 122-32. 

[5] Khaligh A, Li Z, Battery. (2010). Ultracapacitor, fuel cell, and hybrid energy storage systems for electric, hybrid electric, fuel cell, and plug-in hybrid electric vehicles: State of the art. IEEE Transactions on Vehicular Technology 59(6): 2806-14. 

[6] Carter R, Cruden A, Hall PJ. (2012). Optimizing for efficiency or battery life in a battery/supercapacitor electric vehicle. IEEE Transactions on Vehicular Technology 61(4): 1526-33.

[7] Golchoubian P, Azad NL. (2017). Real-time nonlinear model predictive control of a battery–supercapacitor hybrid energy storage system in electric vehicles. IEEE Transactions on Vehicular Technology 66(11): 9678-88.

[8] Shen J, Khaligh A. (2015). A supervisory energy management control strategy in a battery/ultracapacitor hybrid energy storage system. IEEE Transactions on Transportation Electrification 1(3): 223-31.

[9] Choi ME, Kim SW, Seo SW. (2012). Energy management optimization in a battery/supercapacitor hybrid energy storage system. IEEE Transactions on Smart Grid 3(1): 463-72. 

[10] Cao J, Emadi A. (2012). A new battery/ultracapacitor hybrid energy storage system for electric, hybrid, and plug-in hybrid electric vehicles. IEEE Transactions on Power Electronics 27(1): 122-32.