The skills and knowledge gained in this workshop will enable students to carry out regulatory responsibilities related to the administration of the Aircraft Certification and Continued Operational Safety. This course content provides the Civil Aviation Safety Engineers (Systems - Electrical) with the knowledge and skills to conduct oversight of aviation safety, aircraft certification and Continued Operational Safety.
“NuGen Mobility Summit-2019” Paper Title : Determining the State Of Health [SOH] of Li Ion cell Authors: Sushant Mutagekar, Ashok Jhunjhunwala, Prabhjot Kaur Objective Cells age with life. This aging is dependant on various factors like charging/discharging rates, DOD of operation and operating temperature. As the cell ages it undergoes power fade (ability to deliver required power at particular State of Charge [SOC]) and capacity fade (the charge storage capacity of cell). In an Electric Vehicle it is important to know what power shall be demanded from a battery irrespective of what its current SOC is and number of cycles it has undergone. With minimal accuracy and less computational power, it is difficult for a Battery Management System [BMS] to accurately determine SOH; the paper proposes a a precise model that may help.
Battery operated vehicle need accurate management system because of its quick changes in State of charge (SOC) due to aggressive acceleration profiles and regenerative braking. Li-ion battery needs control over its operating area for its safe working. So, the main objective of the proposed system is to develop a BMS having algorithms to estimate accurate SOC, predict degradation parameters, balance individual cells, manage cell temperature, and provide safe area of operation defined by voltage and temperature. Proposed methodology uses Model-based Design approach wherein nonlinear behavior of battery is modeled as Equivalent Circuit Model to compute the SOC and degradation effect on battery to decide the end of life of battery, also performing inductive Active balancing on cells to equalize the charge. proposed algorithms communicate with the vehicle ECU through CAN to assist the driver for runtime estimation, time for battery swapping, Alerts.
In this paper we propose the snow mobility vehicle in order increase the mobility and decrease the risk of accidents for carry food and medicines on snow bounded areas using unmanned tracked vehicle called as snowmobii 2.0. Our unmanned tracked vehicle can transport Food/medicines as well as Defence in snow bounded areas. This unmanned robot can run in loose as well as hard snow due to it have specific featured technology in base wheel(track wheel system) such as hub with outer seals that improve its durability. The proposed snow mobility vehicle is consist of many sophisticated-designed systems such as navigation system, obstacle detection system, communication system, temperature sensing system. Snowmobii 2.0 is easy to get command and enable significant reduction in losses of many solder’s precious lives due to unavailability of food and medicines at that place.
ELECTRIC VEHICLE THERMAL MANAGEMENT SYSTEM FOR HOT CLIMATE REGIONS Rana Tarun*, Yamamoto Yuji, Kumar Ritesh, Bhagatkar Shubhada Pranav Vikas India Private Limited, India Key Words Electric Vehicles (EV); Battery Thermal Management System (BTMS); COP; Electric Vehicle Thermal Management System (EVTMS); BTMS and HVAC System Integration; Thermal System Performance Comparison; Active Liquid Cooling; EV Battery Cooling Research and/or Engineering Questions/Objective Electric Vehicles is the need of time to limit global warming and it is in application at a wide scale in colder or mild climate regions where ambient temperature is limited to mild or moderate level. Its application (Heat pump, CO2) is constrained to cold climates only due to securing better COP for heating function, sacrificing cooling COP of the existing system when operated in Hot Climate Regions, thus limiting its application to nearly half of the automotive user-base.
Introduction: The advent of electric mobility is changing the conventional mobility techniques and with this comes challenges to improve the performance of battery to optimize power consumption in electric vehicles. Objective: This paper would focus on the optimization of battery performance incoherent with vehicle power consumption behavior in terms of efficiency using decision-making ability based on given input signals
Objective It is very important to simulate the battery pack being built to understand its behavior when used in applications especially Electric vehicles (EV). All Li-Ion cells are not the same. They need to be characterized before building any battery pack. Hence modeling the battery pack to simulated its performance in the actual conditions becomes important. Methodology To understand the behavior of cells in the on-field environment, they are tested at various conditions like different rates of charging/discharging, various depth of discharge (DOD), ambient temperature, etc. HPPC test is also performed on cells to derive its RC model equivalent model. GT Suite simulation software is used to model the Li-Ion cell using the testing data. Depending on the pack configuration, the modeled cell is connected in the required series and parallel configuration, to study the battery pack with respect to aging, performance and cooling requirements.
Small electric vehicles are challenging in nature while designing the power train and especially the mounting of batteries within the volume available. In this research, power train of small electric vehicle is designed and it is compared with the electric vehicles. The designed vehicle should meet the requirements of urban car so that it can be preferred in urban mobility. Emphasis is given on studying performance parameters such as motor speed, torque for different urban driving cycles by altering the motor and its no. of poles. Battery pack is designed to fit under the front hood of the vehicle whereas motor is fitted at the rear. Range is estimated using Simulink and it is validated with mathematical calculation using Peukert method performed in MATLAB. It is concluded that the designed vehicle with Switched Reluctance Motor 6/4 configuration of 15 kW, 110 Nm is sufficient to meet the urban car in 2020 targets. NCA battery is preferred for range improvement.