Open Access Open Access  Restricted Access Subscription or Fee Access

Mathematical Model for Ground Electric Vehicle Using Matlab - Simulink

Amit Yadav, D.K Chaturvedi

Abstract


Mathematical modeling of electric vehicle is present in this work. This mathematical modeling gives fast response, accuracy and it show all the function of moving electric vehicle. Also describes the application of MATLAB modeling and simulation. A method is described to extract the model parameters and to approximate estimation of the internal system. The model is validated superimposing the results with the design discharge curves. Finally, the battery model is included in the SimPowerSystem simulation software and is used in the Electric Vehicle (EV) demo. A simplified mathematical model for ground electric vehicle is developed as per the objective. For making the full simulation environment, the control law would also be developed in Simulink and testing would be carried out Finally the control law would be translated in software for intended hardware and real EV will be achieved. Modelling and simulation of systems by using various parameters, software will facilitate the process of designing, constructing and inspecting the vehicle in the real world. One can investigate, design, visualize, and test an object or even if it does not exists

Full Text:

PDF

References


Ahn. J.H. , Kwak. S , and Choi. C, “An integrated machine vision system for multiple human Tracking and silhouette extraction”, pp.573-583, 2006.

Adam.A, Rivlin.E , and Shimshoni.I , “ Computing the sensory uncertainty field of a Vision-based localization sensor ,” proc . Of the IEEE International Conference on Robotics & Automation, pp. 2993-2999, April 2000.

Awad. F and Shamroukh.R , “Human Detection by Intelligent Machine Urban Search and Rescue Using Image Processing and Neural Networks” International Journal of Intelligent Science , pp.4 39-53, 2014.

Burridge.R and Graham, “Providing machine assistance during extra-vehicular activity”, SPIE, 2001.

Betke.M and Gurvits.L , “ Machine Intelligent localization using landmarks ,” IEEE Trans . On Machine and Automation, vol.13, no. 2 pp. 251-263, April 1997.

Bellotto.N and Hu.H, “Vision and laser data fusion for tracking object with a mobile machine”. In proc. IEEE Int. conf. on Machine and Biomimetics (ROBIO), pp. 7-12 China 2016.

Beymer.D and Konolige.K , Tracking object from a mobile platform. In IJCAI-2001 Workshop on Reasoning with Uncertainty in Machine, Seattle, USA, 2001.

Beymer.D and Konolig.K , “Tracking obstacle from a moving platform. Int. Proceeding of 202 int. Symp. On Experimental Machines. pp. 234-244, 2002.

Borenstein.J and Koren.K, “Obstacle Avoidance with Ultrasonic Sensors”. IEEE Journal of Robotics and Automation, vol. RA-4, No.2, pp. 213-218, 1988.

Borenstein. J and Koren. K , “Real- time obstacle avoidance for fast moving machine”, IEEE Transactions on system , Man and Cybernetics B , vol.19 no.5 pp. 1179-1187 , 1989.

Borenstein .J, and Koren. K, “The vector field histogram-fast obstacle avoidance for mobile robots, IEEE Trans. on Robotics and Automation, pp.501-518, 1991.

Barraquand. J and Latombe .J.C, “Machine motion planning: a distributed representation Approach”, International Journal of Robotics Research, vol.10 no.6, pp. 628-649 , 2006.

Bellotto. N and Mak. K, “Multisensor based human tracking for an indoor service robot”, Submitted to IJRR , 2007.

Sandeep Bhatia, Ajay Mudgal, and Amita Soni, “Alive Human Detection Using an Autonomous Mobile Rescue Robot”, Department of Electrical & Electronics, PEC University of Technology, Chandigarh, India vol.no.2, July 2010.

Biswas. J and Veloso .N, “Depth Camera Based Indoor Mobile Machine Localization and Navigation”, in Proc. of ICRA, pp. 1697-1702, 2012.

Coaniciu. D, Ramesh. V and Meer. P, “Kernel-based object tracking”on Pattern Analysis and Machine Intelligent, vol.25 no.5, pp.564-577, May 2003.

Cielniak .G, Treptow. A & Duckett. T, “Quantitative Performance Evaluation of a People Tracking System on a Mobile Robot, Proc. Of ECMR05 (2nd European Conference on Mobile Robots), Ancona, Italy, Sept 2005.

Chaturvedi.D.K, Modeling and Simulation of Systems using MATLAB and Simulink, CRC Press 2002.

Fritsch. J, Kleinehagenbrock. J, and Lang. S, “Multi-modal anchoring for human-machine attraction”, Robotics and Autonomous systems, vol.43 , pp.133-147 , 2003.

Gavrila D.M, “The visual analysis of human movement”. Computer Vision and Understanding, 82-98, 1999.

Gavrila.D.M, “The visual analysis of intelligent machine movement: a survey. Digital Image Understand 73(1): pp.82-98, 1999.

Gavrila.D.M and Philomin.V, “Real-time object detection for smart vehicles”, in IEEE International Conference on Computer Vision, 1999.

Graham .J and Shillcutt. K, “Robot tracking of human subjects in field environment”, Proceedings of the International Symposium on Artificial Intelligence, Robotics, and Automation in space, 2003.

Gonzalez and Woods. R.E, “Digital Image Processing second Edition”,Prentice Hall, New Jersey.

Huang.Z.H and Cohen.F.C , “Affine Invarient B-spline moments for curve Matching IEEE Trans. Image Process 5, 1473-1480, 1996.

Han. H.K , Kim .B.K , and Lee. M , “ Active calibration of the machine / camera pose Using the circular objects,” Trans. on Control , Automation and Systems Engineering (in Korean) , vol.5 , no.3 , pp. 314-323 , April , 1999.

Hall. D.L and Llina .S, editor’s .Handbook of multisensory data fusion. CRC Press, 2001.

Horn. B and Schunck. B, “Determining Optical Flow”. Artificial Intelligence, 17: 185- 203, 1981

Haralick .R.M and Shapiro.S.M, Computer and Machine Vision, Addison-Wesley, 1993.

B. Ilias , R. Nagarajan , and M. Murugappan , “Hospital nurse following machine :hardware development and sensor integration . International Journal of Medical Engineering and Informatics (IJMEI) 6(1): 1-13, Inderscience, ISSN; 1755-0653 (print), 1755-0661 (online), 2014.




DOI: https://doi.org/10.37628/ijacs.v2i2.316

Refbacks

  • There are currently no refbacks.