Qadeer Ahmed

Bio: Qadeer Ahmed is an academic researcher from Ohio State University. The author has contributed to research in topics: Powertrain & Battery (electricity). The author has an hindex of 12, co-authored 94 publications receiving 606 citations. Previous affiliations of Qadeer Ahmed include Jinnah University for Women & Capital University.

2-sliding mode based robust control for 2-DOF helicopter

Abstract: Mass distribution variations in helicopters cause significant adverse effects on helicopter flight. These variations are triggered by unwanted torques. These unwanted torques must be compensated for the sake of smooth and comfortable flight. This paper presents a robust control algorithm to overcome the fore-mentioned problem. The robust control algorithm is based on super twisting based 2-sliding mode control (2-SMC). This scheme offers the solution to cope with torques caused by perturbation in center of gravity (CG) and guarantees smooth flight. The idea has been successfully proven and verified by implementation on the 2-DOF helicopter.

Estimating SI Engine Efficiencies and Parameters in Second-Order Sliding Modes

Abstract: Identification and estimation of immeasurable critical parameters/efficiencies of automotive engine provide significant information to monitor its functions and health. This paper proposes a novel estimation scheme for identifying such parameters. Four of the critical parameters discussed are frictional torque, combustion efficiency, volumetric efficiency, and throttle discharge coefficient. These parameters are estimated from a two-state nonlinear inlet manifold pressure and rotational speed dynamics-based engine model. The estimation scheme utilizes a second-order sliding mode observer based on a super twisting algorithm. The estimation is carried out on a production vehicle equipped with an engine control unit compliant to On-Board Diagnostics II standards. The proposed observers are simple enough for implementation. The estimated parameters have vast application in the area of engine modeling, controller design, and fault diagnosis/prognosis.

Fault Detection and Isolation for Lithium-Ion Battery System Using Structural Analysis and Sequential Residual Generation

Abstract: This paper presents a systematic methodology based on structural analysis and sequential residual generators to design a Fault Detection and Isolation (FDI) scheme for nonlinear battery systems. The faults to be diagnosed are highlighted using a detailed hazard analysis conducted for battery systems. The developed methodology includes four steps: candidate residual generators generation, residual generators selection, diagnostic test construction and fault isolation. State transformation is employed to make the residuals realizable. The simulation results show that the proposed FDI scheme successfully detects and isolates the faults injected in the battery cell with cooling system at different times. In addition, there are no false or missed detections of the faults.Copyright © 2014 by ASME

Virtual Sensors for Automotive Engine Sensors Fault Diagnosis in Second-Order Sliding Modes

Abstract: Automotive engine functions are entirely dependent on installed sensors performance. Any malfunction in the sensors can lead to degraded engine efficiency. This manuscript presents a novel scheme to devise virtual sensors for health monitoring of engine air intake path sensors. The proposed scheme assists in: Sensing of critical immeasurable parameters like Volumetric and Combustion efficiency, development of Virtual Sensor from manifold pressure dynamics for rotational speed and vice versa, Health Monitoring of the manifold pressure and crankshaft sensor. For the suggested scheme, two robust second-order sliding mode observers are employed that require two state mean value engine model based on inlet manifold pressure and rotational speed dynamics. The proposed methodology has the potential of online implementation on any automotive engine after minor tuning. In this paper, the procedure is customized for 1.3 L gasoline engine sensors: Manifold Pressure and Crankshaft sensor. The implementation results demonstrate that all the three mentioned tasks are accomplished efficiently.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Mathematical Theory of Reliability

Abstract: (1966). Mathematical Theory of Reliability. Journal of the Operational Research Society: Vol. 17, No. 2, pp. 213-215.

Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures

Abstract: Lithium (Li)-ion batteries have become the mainstream energy storage solution for many applications, such as electric vehicles (EVs) and smart grids. However, various faults in a Li-ion battery system (LIBS) can potentially cause performance degradation and severe safety issues. Developing advanced fault diagnosis technologies is becoming increasingly critical for the safe operation of LIBS. This article provides a comprehensive review of the mechanisms, features, and diagnosis of various faults in LIBSs, including internal battery faults, sensor faults, and actuator faults. Future trends in the development of fault diagnosis technologies for a safer battery system are presented and discussed.