Neural Network-Based Li-Ion Battery Aging Model at Accelerated C-Rate

Lithium-ion (Li-ion) batteries are widely used in electric vehicles (EVs) because of their high energy density, low self-discharge, and superior performance. Despite this, Li-ion batteries’ performance and reliability become critical as they lose their capacity with increasing charge and discharging cycles. Moreover, Li-ion batteries are subject to aging in EVs due to load variations in discharge. Monitoring the battery cycle life at various discharge rates would enable the battery management system (BMS) to implement control parameters to resolve the aging issue. In this paper, a battery lifetime degradation model is proposed at an accelerated current rate (C-rate). Furthermore, an ideal lifetime discharge rate within the standard C-rate and beyond the C-rate is proposed. The consequence of discharging at an accelerated C-rate on the cycle life of the batteries is thoroughly investigated. Moreover, the battery degradation model is investigated with a deep learning algorithm-based feed-forward neural network (FNN), and a recurrent neural network (RNN) with long short-term memory (LSTM) layer. A comparative assessment of performance of the developed models is carried out and it is shown that the LSTM-RNN battery aging model has superior performance at accelerated C-rate compared to the traditional FNN network

Simulated rotor test apparatus dynamic characteristics in the 80- by 120-foot wind tunnel

A shake test was conducted in the 80 by 120 foot Wind Tunnel at NASA Ames Research Center, using a load frame and dummy weights to simulate the weight of the NASA Rotor Test Apparatus. The simulated hub was excited with broadband random excitation, and accelerometer responses were measured at various locations. The transfer functions (acceleration per unit excitation force as a function of frequency) for each of the accelerometer responses were computed, and the data were analyzed using modal analysis to estimate the model parameters

NLSR: Named Data Link State Routing Protocol

Named Data Networking (NDN) is a fundamental paradigm shift from the current Internet where, packets are forwarded by name instead of the destination IP address. By explicitly naming each packet and signing data, NDN enables some revolutionary features like data authenticity, multicast data delivery, and multipath forwarding with adaptive strategies. For NDN to work well over a network, it requires a routing protocol which will not only need to propagate name reachability in the network, but also compute ranked multipath forwarding entries for each name by ensuring the security of routing exchanges. Moreover, moving from a traditional, long studied, and well-understood IP based thinking process to name based routing makes designing an efficient routing protocol for NDN more challenging. This thesis presents Named-data Link State Routing (NLSR), which propagates name reachability and computes ranked multiple nexthops for forwarding. NLSR also takes advantage of inherent data authenticity features to provide simple yet robust security for routing exchanges.This thesis focuses on discussing four functional design goals of NLSR. First and foremost is designing a naming scheme for routers, routing updates, and routers\u27 cryptographic certificates. The second design goal is to make a rational choice between two available synchronization protocols for disseminating routing updates in NDN. The third goal is designing an efficient algorithm to produce multiple nexthops for each forwarding entry. The fourth and final goal is to produce a self-sufficient design for naming, distributing cryptographic certificates in the network, and deriving trust from those certificates for routing updates.The goal of this thesis is to design and evaluate a routing protocol, which will well serve the needs of NDN. NLSR moves from the conventional IP based routing to name based routing and from single path forwarding to multiple path forwarding. We have evaluated NLSR, and compared to IP link state routing protocol, it offers more efficient routing update propagation, inherent update authentication, and native support of multipath forwarding. NLSR provides a great learning experience to develop an application on top of NDN which requires meticulous consideration in namespace design, careful design of the trust model for data authentication, and most importantly, a mental adjustment to NDN\u27s design philosophy of using interest-data exchanges for routing messages. NLSR is the first distributed routing protocol in NDN for a single authoritative domain and the first step toward developing and extending protocols for inter-domain routing

Simplified fuzzy control for flux-weakening speed control of IPMSM drive

This paper presents a simplified fuzzy logic-based speed control scheme of an interior permanent magnet synchronous motor (IPMSM) above the base speed using a flux-weakening method. In this work, nonlinear expressions of d-axis and q-axis currents of the IPMSM have been derived and subsequently incorporated in the control algorithm for the practical purpose in order to implement fuzzy-based flux-weakening strategy to operate the motor above the base speed. The fundamentals of fuzzy logic algorithms as related to motor control applications are also illustrated. A simplified fuzzy speed controller (FLC) for the IPMSM drive has been designed and incorporated in the drive system to maintain high performance standards. The efficacy of the proposed simplified FLC-based IPMSM drive is verified by simulation at various dynamic operating conditions. The simplified FLC is found to be robust and efficient. Laboratory test results of proportional integral (PI) controller-based IPMSM drive have been compared with the simulated results of fuzzy controller-based flux-weakening IPMSM drive system

EFFECTS OF LAND-USE CHANGE ON THE PROPERTIES OF TOP SOIL OF DECIDUOUS SAL FOREST IN BANGLADESH

This study examined the effects of land use change on the physico-chemical properties of top soil in the deciduous Sal forest of Bangladesh. Relatively less disturbed Sal (Shorea robusta Roxb. Ex Gaertn.) forest stands and the nearby stands those were converted into Acacia (Acacia auriculiformis Benth.) plantation and pineapple (Ananus comosus (L.) Merr.) cultivation were selected to examine the effects of land use change on soil properties. For each land use type, soil samples were collected from 4 locations, 50m distant from each other, as replicates. Soil samples were collected at 0-5, 5-10, and 10-15 cm depths. Soil moisture content, conductivity, pH organic C, total N and total P were determined as soil properties. Leaf litter of Sal, Acacia and pineapple was incubation for 90 and 180 days in independent identical soil in order to examine the effects of plant species through leaf litter on the soil chemical nutrient (N and P) status. Data showed that soil moisture content, conductivity and pH were significantly affected by land use but not by depth. However, soil organic C was affected by both land-use type (P< 0.02) and soil depth (P< 0.003), although no significant interactions appeared between these two factors. Soil total N and P did not differ between land use types but by depth and, N and P contents decreased with the increase of depth. Rates of nutrients (N and P) released from Sal, Acacia and pineapple did not differ significantly among them during incubation. Results of the present study reveal that properties of the top soil of the Madhupur Sal forest are different in their responses to the varying land uses. The findings of this study are thus relevant for the sustainable management of the deciduous Sal forest ecosystems

Drought Vulnerability Assessment Using Geospatial Techniques in Southern Queensland, Australia.

In Australia, droughts are recurring events that tremendously affect environmental, agricultural and socio-economic activities. Southern Queensland is one of the most drought-prone regions in Australia. Consequently, a comprehensive drought vulnerability mapping is essential to generate a drought vulnerability map that can help develop and implement drought mitigation strategies. The study aimed to prepare a comprehensive drought vulnerability map that combines drought categories using geospatial techniques and to assess the spatial extent of the vulnerability of droughts in southern Queensland. A total of 14 drought-influencing criteria were selected for three drought categories, specifically, meteorological, hydrological and agricultural. The specific criteria spatial layers were prepared and weighted using the fuzzy analytical hierarchy process. Individual categories of drought vulnerability maps were prepared from their specific indices. Finally, the overall drought vulnerability map was generated by combining the indices using spatial analysis. Results revealed that approximately 79.60% of the southern Queensland region is moderately to extremely vulnerable to drought. The findings of this study were validated successfully through the receiver operating characteristics curve (ROC) and the area under the curve (AUC) approach using previous historical drought records. Results can be helpful for decision makers to develop and apply proactive drought mitigation strategies

Effect of hydrogen sulphide on liver somatic index and Fulton's condition factor in Mystus nemurus

The growth rate and liver somatic index were significantly (P0.05) in Fulton's condition factor were detected between the exposed fish and the controls. The results revealed that liver somatic index is a more sensitive indicator of hydrogen sulphide toxicity compared to Fulton's condition factor