Optimal power management of hybrid electric vehicles through drivetrain analysis

The inefficient performance of gasoline-engine based vehicles along with high emissions and fuel consumption can be improved through utilization of hybrid electric vehicles (HEVs). The multiple power and energy sources in the hybrid drivetrain can be well managed through an appropriate control strategy that supervises the power distribution. While doing so, the control strategy needs to operate every component optimally in addition to overseeing controlled charge-discharge of battery to obtain efficient energy usage. In this thesis an algorithm has been developed for efficient power division among the various components of a series-parallel (S-P) drivetrain. It has been designed to manage the power flow with the least possible losses while keeping fuel economy at an optimum level and maintaining battery state-of-charge (SOC) in a pre-defined range. The importance of optimizing both engine and motor has been discussed. Analysis has also been presented to show possible benefit of using diesel instead of gasoline engine for hybrid vehicles

Assessment of dietary pattern of adolescents in Himachal Pradesh of India

     Dietary knowledge and access to resources are critical to improve health and nutritional status in a sustainable way. The present study was conducted to assess the dietary pattern and associated intake of different essential nutrients and vitamins by adolescents in Himachal Pradesh of India. A sample of 150 adolescents in the age group of 11-19 years from the two selected blocks (Panchrukhi and Bhawarna) of Kangra district of Himachal Pradesh was selected randomly to collect information on dietary habits, frequency of eating out, type of fat used for cooking, food fads and fallacies and different nutrients intake across genders. It was found that majority of the male and female adolescents took meals three times a day and preferred home prepared foods. Females were mostly vegetarian whereas males were non- vegetarian. Majority of the male and female adolescents liked fried foods compared to pressure and fire wood cooked foods. Adolescents preferred foods fried in raw mustard oil. Majority of the respondents did not have any restrictions and beliefs regarding consumption of any type of food. There was significant difference in the mean intake of different essential nutrients and vitamins between the male and female adolescents reflecting prevalence of disparity in nutritional status across genders. Intake of most of the nutrients and vitamins by male and female adolescents were below the Recommended Dietary Allowances (RDA) of Indian Council of Medical Research.

Drivers of Credit Penetration in Eastern India

This article highlights that the eastern region of India continues to lag behind other regions in harnessing the potential of bank credit as an instrument to promote growth and development, notwithstanding concerted policy efforts to further financial inclusion in the region. While enhancing access to credit remains critical to strengthen credit penetration in the region, empirical findings suggest that factors influencing demand for credit – per capita income, level of industrial activity and availability of infrastructure such as road network and power supply – also matter

Drivers of Credit Penetration in Eastern India

This article highlights that the eastern region of India continues to lag behind other regions in harnessing the potential of bank credit as an instrument to promote growth and development, notwithstanding concerted policy efforts to further financial inclusion in the region. While enhancing access to credit remains critical to strengthen credit penetration in the region, empirical findings suggest that factors influencing demand for credit – per capita income, level of industrial activity and availability of infrastructure such as road network and power supply – also matter

Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms

We consider stochastic approximations of sampling algorithms, such as Stochastic Gradient Langevin Dynamics (SGLD) and the Random Batch Method (RBM) for Interacting Particle Dynamcs (IPD). We observe that the noise introduced by the stochastic approximation is nearly Gaussian due to the Central Limit Theorem (CLT) while the driving Brownian motion is exactly Gaussian. We harness this structure to absorb the stochastic approximation error inside the diffusion process, and obtain improved convergence guarantees for these algorithms. For SGLD, we prove the first stable convergence rate in KL divergence without requiring uniform warm start, assuming the target density satisfies a Log-Sobolev Inequality. Our result implies superior first-order oracle complexity compared to prior works, under significantly milder assumptions. We also prove the first guarantees for SGLD under even weaker conditions such as H\"{o}lder smoothness and Poincare Inequality, thus bridging the gap between the state-of-the-art guarantees for LMC and SGLD. Our analysis motivates a new algorithm called covariance correction, which corrects for the additional noise introduced by the stochastic approximation by rescaling the strength of the diffusion. Finally, we apply our techniques to analyze RBM, and significantly improve upon the guarantees in prior works (such as removing exponential dependence on horizon), under minimal assumptions.Comment: Version 2 considers more results, including those for stochastic gradient lagevin dynamics and the random batch method for interacting particle dynamics, along with the results in the previous version. This also contains 2 additional author