Development of Electrolytes for Si-Graphite Composite Electrodes

The performance of Si-graphite/Li cells and Si-graphite/NMC111 cells has been investigated in 1.2 M LiPF6 /EC:DEC (1/1, w/w) with different electrolyte additives including LiNO3, FEC, and MEC. The addition of additives into electrolytes result in a significant improvement in capacity retention compared to the standard electrolyte for Si-graphite/Li cells. The cells cycled with electrolyte containing 0.5 wt% LiNO3, 5–10 wt% MEC or 10 wt% FEC have high capacity retention, at least 88%, while the cells cycled with standard electrolyte have lower capacity retention, 64%, after 100 cycles. Investigation of Si-graphite/NCM111 cells reveals that the cells cycled in electrolyte containing 0.5 wt% LiNO3 have better capacity retention than cells cycled with 10 wt% FEC, 57.9% vs. 44.6%, respectively. The combination of 10% MEC and LiNO3 further improves the capacity retention of the Si-graphite/NCM111 full cells to 79.9% after 100 cycles which is highest among the electrolytes investigated. Ex-situ surface analyses by XPS and IR-ATR have been conducted to provide a fundamental understanding the composition of the solid-electrolyte interphase (SEI) and its correlation to cycling performance

Capacity Fading Mechanisms of Silicon Nanoparticle Negative Electrodes for Lithium Ion Batteries

A thorough analysis of the evolution of the voltage profiles of silicon nanoparticle electrodes upon cycling has been conducted. The largest changes to the voltage profiles occur at the earlier stages (\u3e 0.16 V vs Li/Li+) of lithiation of the silicon nanoparticles. The changes in the voltage profiles suggest that the predominant failure mechanism of the silicon electrode is related to incomplete delithiation of the silicon electrode during cycling. The incomplete delithiation is attributed to resistance increases during delithiation, which are predominantly contact and solid electrolyte interface (SEI) resistance. The capacity retention can be significantly improved by lowering delithiation cutoff voltage or by introducing electrolyte additives, which generate a superior SEI. The improved capacity retention is attributed to the reduction of the contact and SEI resistance

A Data System for a Rapid Evaluation Class of Subscale Aerial Vehicle

A low cost, rapid evaluation, test aircraft is used to develop and test airframe damage diagnosis algorithms at Langley Research Center as part of NASA's Aviation Safety Program. The remotely operated subscale aircraft is instrumented with sensors to monitor structural response during flight. Data is collected for good and compromised airframe configurations to develop data driven models for diagnosing airframe state. This paper describes the data acquisition system (DAS) of the rapid evaluation test aircraft. A PC/104 form factor DAS was developed to allow use of Matlab, Simulink simulation code in Langley's existing subscale aircraft flight test infrastructure. The small scale of the test aircraft permitted laboratory testing of the actual flight article under controlled conditions. The low cost and modularity of the DAS permitted adaptation to various flight experiment requirements

An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter

Applications of Fault Detection in Vibrating Structures

Structural fault detection and identification remains an area of active research. Solutions to fault detection and identification may be based on subtle changes in the time series history of vibration signals originating from various sensor locations throughout the structure. The purpose of this paper is to document the application of vibration based fault detection methods applied to several structures. Overall, this paper demonstrates the utility of vibration based methods for fault detection in a controlled laboratory setting and limitations of applying the same methods to a similar structure during flight on an experimental subscale aircraft

Citric Acid Based Pre-SEI for Improvement of Silicon Electrodes in Lithium Ion Batteries

Silicon electrodes are of interest to the lithium ion battery industry due to high gravimetric capacity (∼3580 mAh/g), natural abundance, and low toxicity. However, the process of alloying and dealloying during cell cycling, causes the silicon particles to undergo a dramatic volume change of approximately 280% which leads to electrolyte consumption, pulverization of the electrode, and poor cycling. In this study, the formation of an ex-situ artificial SEI on the silicon nanoparticles with citric acid has been investigated. Citric acid (CA) which was previously used as a binder for silicon electrodes was used to modify the surface of the nanoparticles to generate an artificial SEI, which could inhibit electrolyte decomposition on the surface of the silicon nanoparticles. The results suggest improved capacity retention of ∼60% after 50 cycles for the surface modified silicon electrodes compared to 45% with the surface unmodified electrode. Similar improvements in capacity retention are observed upon citric acid surface modification for silicon graphite composite/ LiCoO2 cells