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The vehicle sideslip angle is an important state of vehicle lateral dynamics and its knowledge is crucial for the successful implementation of advanced driver-assistance systems. Measuring the vehicle sideslip angle on a production vehicle is challenging because of the exorbitant price of a physical sensor. This paper aims to present a novel framework for virtually sensing/estimating the vehicle sideslip angle. The desired level of accuracy for the estimator is to be within +/− 0.2 degree of the actual sideslip angle of the vehicle. This will make the precision of the proposed estimator at par with expensive commercially available sensors used for physically measuring the vehicle sideslip angle.

The proposed estimator uses an adaptive tire model in conjunction with a model-based observer. The performance of the estimator is evaluated through experimental tests on a rear-wheel drive vehicle.

Detailed experimental results show that the developed system can reliably estimate the vehicle sideslip angle during both steady state and transient maneuvers, within the desired accuracy levels.

This paper presents a novel framework for vehicle sideslip angle estimation. The presented framework combines an adaptive tire model, an unscented Kalman filter-based axle force observer and data from tire mounted sensors. Tire model adaptation is achieved by making extensions to the magic formula, by accounting for variations in the tire inflation pressure, load, tread-depth and temperature. Predictions with the adapted tire model were validated by running experiments on the Flat-Trac® machine. The benefits of using an adaptive tire model for sideslip angle estimation are demonstrated through experimental tests. The performance of the observer is satisfactory, in both transient and steady state maneuvers. Future work will focus on measuring tire slip angle and road friction information using tire mounted sensors and using that information to further enhance the robustness of the vehicle sideslip angle observer.

The issue of mounting non-performing assets (NPAs) in Indian banking industry is serious and attracting attention of academia and policy planners. Thus, the purpose of this paper is to test the hypothesis whether NPAs in Indian commercial banking have reached at alarming state where they start affecting the technical efficiency levels adversely or not.

The efficiency score have been computed using case model (model with NPAs as bad/undesirable output) vs control model (model without NPAs as bad/undesirable output) methodology under meta-frontier data envelopment analysis framework.

It has been noticed that the effect of NPAs on overall technical efficiency and its various components is insignificant. The comparison of the case models (i.e. model with NPAs as bad output) with the control models (i.e. model without NPAs) reveals insignificant difference in average efficiency scores and rank distribution of commercial banks. The major source of inefficiency is technology gap (i.e. structure, setup and objectives of banking) among public, domestic private and foreign private categories of banks.

Though NPAs are increasing in Indian banking industry and specifically in Indian public sector banks because of their compulsory lending to priority sector yet the banks have huge scope to extend credit to priority sector as the NPAs have not reached at alarming stage where they start affecting adversely the efficiency performance.

Given the fact that the banking penetrations, structure and objectives differ significantly across ownership, separate frontiers for each ownership (public, private and foreign banks) category has been used to evaluate the technical efficiency levels of 81 commercial banks operating in India over the period 2005 to 2013.