The document describes a battery management system that includes:
- A smart battery with a controller that calculates state of charge and communicates with a local host system, and a control circuit that regulates current and charge/discharge.
- A management system with flexible architecture, accurate state of charge calculation, intelligent current control for balancing and safety, compatibility with multiple platforms, and cloud computing for data analysis and display.
- The system monitors and controls lithium-ion batteries in applications like electric vehicles through current control, data communication, and a control panel that displays state of charge.
India rubber-industry-forum-2016. Kartik Srinivas has a Master's degree in Mechanical Engineering from Wright State University, USA. He is a consulting mechanical engineer with extensive background and experience in product engineering using simulation technologies and mechanical testing. Kartik provides Finite Element Analysis (FEA) solutions to a broad range of industries and is well versed with material and product testing as per ASTM and ISO standards. Kartik has 7 technical papers to his credit and has been the chair of the session on automotive composites at the SAE World Congress from 2006 through 2011. He has volunteered as a reviewer for the Journal of Rubber Chemistry and Technology
Tyres are the most important component of every vehicle. The performance of your vehicle mostly depends upon the tyre. Some points are considered in this infographic for proper maintenance of the vehicle.
Meetup 16 dec data driven process to optimizationAndra Baragan
In this presentation you will learn the basic steps into building your own Conversion Optimization program and the way you can use data to your advantage.
IoT Based Battery Management System in Electric Vehicles.pdfKaty Slemon
Explore India's most advanced cloud platform- IONDASH, responsible for monitoring the performance of battery management system in electric vehicles.
Depending on battery type and application, Lead Acid batteries have a design life that can range from 5 to 20 years. That design life estimation is based on the battery being maintained in accordance with recommended practices, operating under ideal conditions and ensuring that any individual failing units are replaced before they impact the other units in the string.
However, in most installations, those conditions are seldom met, and the actual life of a battery may be closer to half of the published design life. This potential for failure has been confirmed in a number of studies over the years. In fact, in one Ponemon study into Data Center failures, the UPS Battery was responsible for over 50% of the reported outages. This data, and the uncertainty of most operating environments, confirms why battery monitoring is an essential part of maintaining today’s systems.
Anne McNelis: Intelligent Power Controller Development for Human Deep Space ...EnergyTech2015
EnergyTech2015.com
SPACE POWER SYSTEMS
Track 2 Session 4 Moderator: James Soeder
This session explored power technologies being developed to enable more advanced deep space missions including; unique power systems, autonomous and intelligent control and real time simulation
Ms Anne McNellis: Paper 1: NASA Intelligent Power Control,
Dr Benjamin Loop: Paper 2: Real Time Simulation for NASA Intelligent Power Control Development
Dr Brad Glenn: Paper 3: Helm Algorithm Development for NASA Intelligent Power Control
Inter-controller Traffic in ONOS Clusters for SDN Networks Paolo Giaccone
In distributed SDN architectures, the network is controlled by a cluster of multiple controllers. This distributed ap- proach permits to meet the scalability and reliability requirements of large operational networks. Despite that, a logical centralized view of the network state should be guaranteed, enabling the simple development of network applications. Achieving a consis- tent network state requires a consensus protocol, which generates control traffic among the controllers whose timely delivery is crucial for network performance.
We focus on the state-of-art ONOS controller, designed to scale to large networks, based on a cluster of self-coordinating controllers, and concentrate on the inter-controller control traffic. Based on real traffic measurements, we develop a model to quan- tify the traffic exchanged among the controllers, which depends on the topology of the controlled network. This model is useful to design and dimension the control network interconnecting the controllers.
The Design of Multi-Platforms Rail Intelligence Flatness Detection SystemIJRESJOURNAL
ABSTRACT: In this paper,we design a Multi-platforms intelligent system for flatness detection of rail welding headbased on thedevelopment environment of Android software .The system uses a STM32 chip as control core, a handheld smart terminal or personal computer as the carrier. The datas transmitted to intelligent terminal or computer through the bluetooth communication technology are processed rapidly, the data curve is drawed and the flatness characteristic parameters of the measured rail welding head is identified. The system provides a friendly intuitive monitoring and operation interface, has the characteristics of fast, reliable, energy saving, high accuracy, etc.
A multiprocessor system consists of multiple processing units connected via some interconnection network plus the software needed to make the processing units work together.
India rubber-industry-forum-2016. Kartik Srinivas has a Master's degree in Mechanical Engineering from Wright State University, USA. He is a consulting mechanical engineer with extensive background and experience in product engineering using simulation technologies and mechanical testing. Kartik provides Finite Element Analysis (FEA) solutions to a broad range of industries and is well versed with material and product testing as per ASTM and ISO standards. Kartik has 7 technical papers to his credit and has been the chair of the session on automotive composites at the SAE World Congress from 2006 through 2011. He has volunteered as a reviewer for the Journal of Rubber Chemistry and Technology
Tyres are the most important component of every vehicle. The performance of your vehicle mostly depends upon the tyre. Some points are considered in this infographic for proper maintenance of the vehicle.
Meetup 16 dec data driven process to optimizationAndra Baragan
In this presentation you will learn the basic steps into building your own Conversion Optimization program and the way you can use data to your advantage.
IoT Based Battery Management System in Electric Vehicles.pdfKaty Slemon
Explore India's most advanced cloud platform- IONDASH, responsible for monitoring the performance of battery management system in electric vehicles.
Depending on battery type and application, Lead Acid batteries have a design life that can range from 5 to 20 years. That design life estimation is based on the battery being maintained in accordance with recommended practices, operating under ideal conditions and ensuring that any individual failing units are replaced before they impact the other units in the string.
However, in most installations, those conditions are seldom met, and the actual life of a battery may be closer to half of the published design life. This potential for failure has been confirmed in a number of studies over the years. In fact, in one Ponemon study into Data Center failures, the UPS Battery was responsible for over 50% of the reported outages. This data, and the uncertainty of most operating environments, confirms why battery monitoring is an essential part of maintaining today’s systems.
Anne McNelis: Intelligent Power Controller Development for Human Deep Space ...EnergyTech2015
EnergyTech2015.com
SPACE POWER SYSTEMS
Track 2 Session 4 Moderator: James Soeder
This session explored power technologies being developed to enable more advanced deep space missions including; unique power systems, autonomous and intelligent control and real time simulation
Ms Anne McNellis: Paper 1: NASA Intelligent Power Control,
Dr Benjamin Loop: Paper 2: Real Time Simulation for NASA Intelligent Power Control Development
Dr Brad Glenn: Paper 3: Helm Algorithm Development for NASA Intelligent Power Control
Inter-controller Traffic in ONOS Clusters for SDN Networks Paolo Giaccone
In distributed SDN architectures, the network is controlled by a cluster of multiple controllers. This distributed ap- proach permits to meet the scalability and reliability requirements of large operational networks. Despite that, a logical centralized view of the network state should be guaranteed, enabling the simple development of network applications. Achieving a consis- tent network state requires a consensus protocol, which generates control traffic among the controllers whose timely delivery is crucial for network performance.
We focus on the state-of-art ONOS controller, designed to scale to large networks, based on a cluster of self-coordinating controllers, and concentrate on the inter-controller control traffic. Based on real traffic measurements, we develop a model to quan- tify the traffic exchanged among the controllers, which depends on the topology of the controlled network. This model is useful to design and dimension the control network interconnecting the controllers.
The Design of Multi-Platforms Rail Intelligence Flatness Detection SystemIJRESJOURNAL
ABSTRACT: In this paper,we design a Multi-platforms intelligent system for flatness detection of rail welding headbased on thedevelopment environment of Android software .The system uses a STM32 chip as control core, a handheld smart terminal or personal computer as the carrier. The datas transmitted to intelligent terminal or computer through the bluetooth communication technology are processed rapidly, the data curve is drawed and the flatness characteristic parameters of the measured rail welding head is identified. The system provides a friendly intuitive monitoring and operation interface, has the characteristics of fast, reliable, energy saving, high accuracy, etc.
A multiprocessor system consists of multiple processing units connected via some interconnection network plus the software needed to make the processing units work together.
BATTERY MANAGEMENT SYSTEM (BMS) IN ELECTRIC VEHICLESBhagavathyP
Why we need BMS?
General function of BMS
Block diagram of BMS
Battery pack – Voltage, Current, Temperature and Isolation sensing
HV contactor control
BMS communications interface
Estimation of energy and power and SOC
Methods to find SOC
Cell Balancing
Relationship between SOC and DOD
2. 11/19/2016www.itu.edu
2Battery Management System
Current Control
Data Communication
Control
Lithium Ion
Battery
Control Panel
SoC Display
Cloud Server
Database
Smart Phone
SoC Display
Smart Battery
Battery Bank
Local Host
System
CAN-BUS
4. Battery Management System
• System Features Highlight
• Flexible architecture supports single cell battery or battery pack management.
• Accurate State of Charge(SoC) calculation.
• Intelligent Current Control for balancing and safety.
• Compatible with different platform: Windows, Linux and any other Embedded
Linux System.
• Powerful Cloud computing for data analysis and display.
11/19/2016www.itu.edu
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