Sensorless Induction Motor Drive Using Indirect Vector Controller and Sliding-Mode Observer for Electric Vehicles

This paper presents a sensorless control system for an electric-vehicle (EV) induction-motor (IM) drive embedded with an indirect vector controller and a fixed-boundary-layer sliding-mode (FBLSM) observer. No speed or even voltage measurements are required. This novel FBLSM observer could accurately estimate the speed and flux even without known load torque, where chattering on estimations due to switching functions in normal sliding-mode observers is almost completely eliminated. The proof of observability in a wide speed range (including very low speeds) is given. The indirect vector controller with feedforward compensation is responsible for tracking motor speed or torque commands, which manages to accelerate algorithm processing and to enhance transient performance. The experimental results based on a high-power driver-load motor configuration validate the accuracy of the observer and the dynamical performance of the controller under multitrapezoidal speed and vehicle driving cycle torque-speed commands, taking into consideration unexpected parameter disturbances .

[1]  Antonios G. Kladas,et al.  Internal Permanent Magnet Motor Design for Electric Vehicle Drive , 2010, IEEE Transactions on Industrial Electronics.

[2]  P. T. Krein,et al.  Markov Reliability Modeling for Induction Motor Drives Under Field-Oriented Control , 2012, IEEE Transactions on Power Electronics.

[3]  Enrique Romero-Cadaval,et al.  Electric vehicle battery charger for smart grids , 2012 .

[4]  Suman Maiti,et al.  An Alternative Adaptation Mechanism for Model Reference Adaptive System Based Sensorless Induction Motor Drive , 2010 .

[5]  Teresa Orlowska-Kowalska,et al.  Stator-Current-Based MRAS Estimator for a Wide Range Speed-Sensorless Induction-Motor Drive , 2010, IEEE Transactions on Industrial Electronics.

[6]  Eric Woirgard,et al.  Principle, design and experimental validation of a flywheel-battery hybrid source for heavy-duty electric vehicles , 2007 .

[7]  Andrew Burke,et al.  Ultracapacitor technologies and application in hybrid and electric vehicles , 2009 .

[8]  Moez Ghariani,et al.  Sliding mode control and neuro-fuzzy network observer for induction motor in EVs applications , 2011 .

[9]  Hamid A. Toliyat,et al.  DSP-Based Sensorless Electric Motor Fault Diagnosis Tools for Electric and Hybrid Electric Vehicle Powertrain Applications , 2009, IEEE Transactions on Vehicular Technology.

[10]  Juan Dixon,et al.  Electric Vehicle Using a Combination of Ultracapacitors and ZEBRA Battery , 2010, IEEE Transactions on Industrial Electronics.

[11]  R. Neji,et al.  Induction machine DTC optimization using artificial intelligence for EV's applications , 2011, Eighth International Multi-Conference on Systems, Signals & Devices.

[12]  Diana Golodnitsky,et al.  Parameter analysis of a practical lithium- and sodium-air electric vehicle battery , 2011 .

[13]  Jorge Moreno,et al.  Ultracapacitor-Based Auxiliary Energy System for an Electric Vehicle: Implementation and Evaluation , 2007, IEEE Transactions on Industrial Electronics.

[14]  Jonq-Chin Hwang,et al.  Digital signal processor-based probabilistic fuzzy neural network control of in-wheel motor drive for light electric vehicle , 2012 .

[15]  Malek Ghanes,et al.  Cascade and high-gain observers comparison for sensorless closed-loop induction motor control , 2008 .

[16]  Cristian De Angelo,et al.  Online Sensorless Induction Motor Temperature Monitoring , 2010, IEEE Transactions on Energy Conversion.

[17]  Yee-Pien Yang,et al.  An Electric Gearshift With Ultracapacitors for the Power Train of an Electric Vehicle With a Directly Driven Wheel Motor , 2007, IEEE Transactions on Vehicular Technology.

[18]  James Foreman-Peck,et al.  The Electric Vehicle: Technology and Expectations in the Automobile Age , 2005 .

[19]  Sung-Ho Hwang,et al.  Vehicle Stability Enhancement of Four-Wheel-Drive Hybrid Electric Vehicle Using Rear Motor Control , 2008, IEEE Transactions on Vehicular Technology.

[20]  Alireza Khaligh,et al.  Influence of Battery/Ultracapacitor Energy-Storage Sizing on Battery Lifetime in a Fuel Cell Hybrid Electric Vehicle , 2009, IEEE Transactions on Vehicular Technology.

[21]  Bing-Gang Cao,et al.  Neural network sliding mode control based on on-line identification for electric vehicle with ultracapacitor-battery hybrid power , 2009 .

[22]  Binggang Cao,et al.  Robust control for regenerative braking of battery electric vehicle , 2008 .

[23]  M. M. Khater,et al.  Very low speed and zero speed estimations of sensorless induction motor drives , 2010 .