Artificial Intelligence (AI) is becoming necessary today automotive world. The talk (presented in Azuga on 1st July in the AI & ML meetup) includes the major areas where AI is applied and the challenges faced in applying AI.
OBDII data generated by a vehicle sensor network can be considered as a canonical proxy for Industrial IoT. Vehicle analytics, in addition to being useful in its own right (e.g. vehicle health monitoring, diagnostics, driver behavior modeling etc.), exhibits the same data characteristics (e.g. highly nonlinear data that varies rapidly in real-time, time delay effects in the data etc.) as an Industrial IoT application. In this case study, we demonstrate our analytics capabilities on a passenger car OBDII data. In particular, we demonstrate how one can use an "AI sensor" - a prediction system in places where no direct sensor measurement is available. Anand Deshpande Aniruddha Pant
Permanent magnet direct current motors (PMDCM) are widely used in various applications such as space technologies, personal computers, medical, military, robotics, electrical vehicles, etc. In this paper, the mathematical model of PMDCM is designed and simulated using MATLAB software. The PMDCM speed is controlled using rate feedback controller due to its ability of improving system damping. To improve the controller performance, it’s parameters are tuned using genetic algorithm (GA) and direct search (DS) techniques. The tuning process based on different performance criteria. The most four common performance criteria used in this paper are JIAE (Integral of Absolute Error), JISE (Integral of Square Error), JITAE (Integral of Time-Weighted Absolute Error), and JITSE (Integral of Time-Weighted Square Error). The results obtained from these evolutionary techniques are compared. The results show an obvious improvement in system performance including enhancing the transient and steady state of PMDCM speed responses for all performance criteria.
Low cost Real Time Centralized Speed Control of DC Motor Using Lab View -NI U...IJPEDS-IAES
DC motors are an outstanding portion of apparatus used in automotive and automation industrial applications requiring variable speed and load characteristics, due to its ease of controllability. Creating an interface control system for multi DC motor drive operations with centralized speed control, from small-scale models to large industrial applications is in much demand. By using Lab VIEW (laboratory virtual instrument engineering workbench) as the motor controller, we can control a DC motor for multiple purposes using single software environment. The aim of this paper is to propose the centralized speed control of DC motor using Lab VIEW. Here, Lab VIEW is used for simulating the motor, whereas the input armature voltage of the DC motor is controlled using a virtual Knob in Lab VIEW software. The hardware part of the system (DC motor) and the software (in personal computer) are interfaced using a data acquisition card (DAQ) -Model PCI- 6024E. The voltage and Speed response is obtained using LABVIEW software. Using this software, the speed of a group of motors can be controlled from different locations using remote telemetry. The proposed work also focuses on controlling the speed of the individual DC motor using PWM scheme (Duty cycle based Square wave generation) and DAQ. With the help of the DAQ along with Lab VIEW front panel window, the DC motor speed and directions can be changed easily in remote way. In order to test the proposed system the laboratory model for an80W DC motor group (multi drive) is developed for different angular displacements and directions of the motor. The simulation model and experimental results conforms the advantages and robustness of the proposed centralized speed control.
OBDII data generated by a vehicle sensor network can be considered as a canonical proxy for Industrial IoT. Vehicle analytics, in addition to being useful in its own right (e.g. vehicle health monitoring, diagnostics, driver behavior modeling etc.), exhibits the same data characteristics (e.g. highly nonlinear data that varies rapidly in real-time, time delay effects in the data etc.) as an Industrial IoT application. In this case study, we demonstrate our analytics capabilities on a passenger car OBDII data. In particular, we demonstrate how one can use an "AI sensor" - a prediction system in places where no direct sensor measurement is available. Anand Deshpande Aniruddha Pant
Permanent magnet direct current motors (PMDCM) are widely used in various applications such as space technologies, personal computers, medical, military, robotics, electrical vehicles, etc. In this paper, the mathematical model of PMDCM is designed and simulated using MATLAB software. The PMDCM speed is controlled using rate feedback controller due to its ability of improving system damping. To improve the controller performance, it’s parameters are tuned using genetic algorithm (GA) and direct search (DS) techniques. The tuning process based on different performance criteria. The most four common performance criteria used in this paper are JIAE (Integral of Absolute Error), JISE (Integral of Square Error), JITAE (Integral of Time-Weighted Absolute Error), and JITSE (Integral of Time-Weighted Square Error). The results obtained from these evolutionary techniques are compared. The results show an obvious improvement in system performance including enhancing the transient and steady state of PMDCM speed responses for all performance criteria.
Low cost Real Time Centralized Speed Control of DC Motor Using Lab View -NI U...IJPEDS-IAES
DC motors are an outstanding portion of apparatus used in automotive and automation industrial applications requiring variable speed and load characteristics, due to its ease of controllability. Creating an interface control system for multi DC motor drive operations with centralized speed control, from small-scale models to large industrial applications is in much demand. By using Lab VIEW (laboratory virtual instrument engineering workbench) as the motor controller, we can control a DC motor for multiple purposes using single software environment. The aim of this paper is to propose the centralized speed control of DC motor using Lab VIEW. Here, Lab VIEW is used for simulating the motor, whereas the input armature voltage of the DC motor is controlled using a virtual Knob in Lab VIEW software. The hardware part of the system (DC motor) and the software (in personal computer) are interfaced using a data acquisition card (DAQ) -Model PCI- 6024E. The voltage and Speed response is obtained using LABVIEW software. Using this software, the speed of a group of motors can be controlled from different locations using remote telemetry. The proposed work also focuses on controlling the speed of the individual DC motor using PWM scheme (Duty cycle based Square wave generation) and DAQ. With the help of the DAQ along with Lab VIEW front panel window, the DC motor speed and directions can be changed easily in remote way. In order to test the proposed system the laboratory model for an80W DC motor group (multi drive) is developed for different angular displacements and directions of the motor. The simulation model and experimental results conforms the advantages and robustness of the proposed centralized speed control.
Altitude SF 2017: Granular, Precached, & Under BudgetFastly
New technologies like Service Workers and H/2 are making it possible to finally load code into our applications proportionate to what’s in view. These approaches require smarter frameworks and better tools, but enable us to once again write (roughly) what we send to users. Alex discusses the challenges and benefits of adopting these emerging approaches to app construction and delivery.
Data-Driven Security Assessment of Power Grids Based on Machine Learning Appr...Power System Operation
Security assessment is a fundamental function for both short-term and long-term power system operations. The data-driven security assessment (DSA) can provide system stability margin without the need for detailed dynamic simulation. DSA is very helpful for control room applications such as online security assessment and day ahead or real-time dispatch scheduling with regard to system security constraints.
This paper investigates a data-driven security assessment of electric power grids based on machine learning. Multivariate random forest regression is used as the machine learning algorithm because of its high robustness to the input data. Three stability issues are analyzed using the proposed machine learning tool: transient stability, frequency stability, and small-signal stability. The estimation values from the machine learning tool are compared with those from dynamic simulations. Results show that the proposed machine learning tool can effectively predict the stability margins for the aforementioned three stabilities.
Data-Driven Security Assessment of Power Grids Based on Machine Learning Appr...Power System Operation
Security assessment is a fundamental function for both short-term and long-term power system operations. The data-driven security assessment (DSA) can provide system stability margin without the need for detailed dynamic simulation. DSA is very helpful for control room applications such as online security assessment and day ahead or real-time dispatch scheduling with regard to system security constraints.
Android devices running on battery need to be optimized for power.
When taking a look at the CPU this optimization starts typically with the race to idle, meaning to go to finish the workload as fast as possible. However typical Android devices are running on a SoC with many other parts like GPU, hardware decoders, sensors, 2G/3G/4G/Wifi modules...
All these parts need to be optimized to reduce the power consumption, but the biggest part of the problem/solution are applications themselves.
Guessing what software is actually causing high power consumption and mitigating it aren't simple tasks. In this session You will explore typical causes of high power consumption, how to debug them and provide possible solutions.
Android provides a number of APIs, OS tricks, and developer tools around power consumption, you will also get to know, learn, and understand them through this talk.
How to find defects early and increase the reliability of software systemsRAKESH RANA
How to find defects early and increase the reliability of software systems
Using Fault Bypass Modeling to improve rapid prototyping and combining fault injection with mutation testing for early identification of safety defects
Presented at:
2nd Workshop on Software-Based Methods for Robust Embedded Systems (SOBRES '13), Sep-2013, Koblenz, Germany
Get full text of publication at:
http://rakeshrana.website/index.php/work/publications/
SurfClipse-- An IDE based context-aware Meta Search Engine (ERA Track)Masud Rahman
Traditional web search forces the developers to leave their working environments and look for solutions in the web browsers. It often does not consider the context of their programming problems. The context-switching between the web browser and the working environment is time-consuming and distracting, and the keyword-based traditional search often does not help much in problem solving. In this paper, we propose an Eclipse IDE-based web search solution that collects the data from three web search APIs– Google, Yahoo, Bing and a programming Q & A site– StackOverflow. It then provides search results within IDE taking not only the content of the selected error into account but also the problem context, popularity and search engine recommendation of the result links. Experiments with 25 runtime errors and exceptions show that the proposed ap- proach outperforms the keyword-based search approaches with a recommendation accuracy of 96%. We also validate the results with a user study involving five prospective participants where we get a result agreement of 64.28%. While the preliminary results are promising, the approach needs to be further validated with more errors and exceptions followed by a user study with more participants to establish itself as a complete IDE-based web search solution.
KonfHub is a one-stop ticketing & event management platform for online, hybrid and in-person events.
In-built features to drive audience to your events & make your events more engaging and effective.
This presentation shows the features, benefits and pricing aspects of KonfHub.
Functional Thinking for Java Developers (presented in Javafest Bengaluru)KonfHubTechConferenc
Moving to functional programming can result in significantly better code and productivity gains. However, it requires a paradigm shift: you need to move away from imperative and object-oriented thinking to start thinking functionally.
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New technologies like Service Workers and H/2 are making it possible to finally load code into our applications proportionate to what’s in view. These approaches require smarter frameworks and better tools, but enable us to once again write (roughly) what we send to users. Alex discusses the challenges and benefits of adopting these emerging approaches to app construction and delivery.
Data-Driven Security Assessment of Power Grids Based on Machine Learning Appr...Power System Operation
Security assessment is a fundamental function for both short-term and long-term power system operations. The data-driven security assessment (DSA) can provide system stability margin without the need for detailed dynamic simulation. DSA is very helpful for control room applications such as online security assessment and day ahead or real-time dispatch scheduling with regard to system security constraints.
This paper investigates a data-driven security assessment of electric power grids based on machine learning. Multivariate random forest regression is used as the machine learning algorithm because of its high robustness to the input data. Three stability issues are analyzed using the proposed machine learning tool: transient stability, frequency stability, and small-signal stability. The estimation values from the machine learning tool are compared with those from dynamic simulations. Results show that the proposed machine learning tool can effectively predict the stability margins for the aforementioned three stabilities.
Data-Driven Security Assessment of Power Grids Based on Machine Learning Appr...Power System Operation
Security assessment is a fundamental function for both short-term and long-term power system operations. The data-driven security assessment (DSA) can provide system stability margin without the need for detailed dynamic simulation. DSA is very helpful for control room applications such as online security assessment and day ahead or real-time dispatch scheduling with regard to system security constraints.
Android devices running on battery need to be optimized for power.
When taking a look at the CPU this optimization starts typically with the race to idle, meaning to go to finish the workload as fast as possible. However typical Android devices are running on a SoC with many other parts like GPU, hardware decoders, sensors, 2G/3G/4G/Wifi modules...
All these parts need to be optimized to reduce the power consumption, but the biggest part of the problem/solution are applications themselves.
Guessing what software is actually causing high power consumption and mitigating it aren't simple tasks. In this session You will explore typical causes of high power consumption, how to debug them and provide possible solutions.
Android provides a number of APIs, OS tricks, and developer tools around power consumption, you will also get to know, learn, and understand them through this talk.
How to find defects early and increase the reliability of software systemsRAKESH RANA
How to find defects early and increase the reliability of software systems
Using Fault Bypass Modeling to improve rapid prototyping and combining fault injection with mutation testing for early identification of safety defects
Presented at:
2nd Workshop on Software-Based Methods for Robust Embedded Systems (SOBRES '13), Sep-2013, Koblenz, Germany
Get full text of publication at:
http://rakeshrana.website/index.php/work/publications/
SurfClipse-- An IDE based context-aware Meta Search Engine (ERA Track)Masud Rahman
Traditional web search forces the developers to leave their working environments and look for solutions in the web browsers. It often does not consider the context of their programming problems. The context-switching between the web browser and the working environment is time-consuming and distracting, and the keyword-based traditional search often does not help much in problem solving. In this paper, we propose an Eclipse IDE-based web search solution that collects the data from three web search APIs– Google, Yahoo, Bing and a programming Q & A site– StackOverflow. It then provides search results within IDE taking not only the content of the selected error into account but also the problem context, popularity and search engine recommendation of the result links. Experiments with 25 runtime errors and exceptions show that the proposed ap- proach outperforms the keyword-based search approaches with a recommendation accuracy of 96%. We also validate the results with a user study involving five prospective participants where we get a result agreement of 64.28%. While the preliminary results are promising, the approach needs to be further validated with more errors and exceptions followed by a user study with more participants to establish itself as a complete IDE-based web search solution.
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In-built features to drive audience to your events & make your events more engaging and effective.
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"Azuga A Safety Company: Data Science Saving Lives" presented by Ashish Kumar Jha, Principal Software Engineer at Azuga, Inc.
Azuga is not just a telemetry company, our prime focus is towards the safety of our customers (Driver, vehicles and other assets). Every day thousands of people lose their lives due to preventable road accidents, we at Azuga use our cutting edge data science models to prevent these accidents resulting in a safer world. Join us in an interactive session where we will explore these use cases and demonstrate data science in Azuga.
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Self-supervised learning (SSL) is behind some of the latest AI breakthroughs. By enabling learning from vast amounts of unlabeled data, rather than relying on carefully annotated datasets, it has unlocked the potential of AI across Natural language processing, audio and computer vision. The talk covers how it is being used for vision tasks.
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AI, or artificial intelligence, is powering a massive shift in how engineers, scientists, and programmers develop and improve products and services. 85% of executives expect to gain or strengthen their competitive advantage through the use of AI, but is AI really poised to transform your research, products, or business?
Learn how AI system can be designed to perceive its environment, make decisions, and take action. Get an overview of AI for engineers, and discover the ways in which it fits into an engineering workflow. You will also learn how MATLAB and Simulink® are giving engineers and scientists AI capabilities that were once available only to highly-specialized software developers and Data Scientists.
Generative AI models, such as GANs and VAEs, have the potential to create realistic and diverse synthetic data for various applications, from image and speech synthesis to drug discovery and language modeling. However, training these models can be challenging due to the instability and mode collapse issues that often arise. In this workshop, we will explore how stable diffusion, a recent training method that combines diffusion models and Langevin dynamics, can address these challenges and improve the performance and stability of generative models. We will use a pre-configured development environment for machine learning, to run hands-on experiments and train stable diffusion models on different datasets. By the end of the session, attendees will have a better understanding of generative AI and stable diffusion, and how to build and deploy stable generative models for real-world use cases.
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A quick recap of the year that was 2021. We conducted several events last year, with great participation and engagement from you. We are super excited to show you what we have lined up for this year!
Utilocate offers a comprehensive solution for locate ticket management by automating and streamlining the entire process. By integrating with Geospatial Information Systems (GIS), it provides accurate mapping and visualization of utility locations, enhancing decision-making and reducing the risk of errors. The system's advanced data analytics tools help identify trends, predict potential issues, and optimize resource allocation, making the locate ticket management process smarter and more efficient. Additionally, automated ticket management ensures consistency and reduces human error, while real-time notifications keep all relevant personnel informed and ready to respond promptly.
The system's ability to streamline workflows and automate ticket routing significantly reduces the time taken to process each ticket, making the process faster and more efficient. Mobile access allows field technicians to update ticket information on the go, ensuring that the latest information is always available and accelerating the locate process. Overall, Utilocate not only enhances the efficiency and accuracy of locate ticket management but also improves safety by minimizing the risk of utility damage through precise and timely locates.
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...Crescat
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
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Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
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👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
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✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-genie-review
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✅100% Easy-to-Use, Newbie-Friendly Technology
✅30-Days Money-Back Guarantee
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
#AIGenieApp #AIGenieBonus #AIGenieBonuses #AIGenieDemo #AIGenieDownload #AIGenieLegit #AIGenieLiveDemo #AIGenieOTO #AIGeniePreview #AIGenieReview #AIGenieReviewandBonus #AIGenieScamorLegit #AIGenieSoftware #AIGenieUpgrades #AIGenieUpsells #HowDoesAlGenie #HowtoBuyAIGenie #HowtoMakeMoneywithAIGenie #MakeMoneyOnline #MakeMoneywithAIGenie
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
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The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
3. SAE INTERNATIONAL
Dr. Vivek Venkobarao
Paper # (if applicable) 3
Education:
Ph.D in Electrical Engineering
Innovation and Entrepreneurship Certificate, Stanford University
Energy Innovation and Emerging Technologies, ‘Stanford University
Data science and big data analytics: Making data driven decisions MIT University
Publications:
Has 35 papers in international conferences and journals published
IEEE Senior Member- Execom member of CT and TEMS
Co-Author “Handbook of Research on Emerging Technologies for Electrical Power Planning,
Analysis, and Optimization“ from leading international publisher
10 Patents granted in US,Germany and India
4. SAE INTERNATIONAL
Non Linear system identification
Mathematical model of a system from
measurements of the inputs and outputs.
Models are developed - data gathering,
parameter identification, model
development and validation
Paper # (if applicable) 4
6. SAE INTERNATIONAL
What to check in a measurement
Paper # (if applicable) 6
Measurements
Majority under
sampling
Minority
Oversampling
7. SAE INTERNATIONAL
Where AI/ML in Embedded systems
Paper # (if applicable) 7
Learning Techniques for embedded system
Automated Calibration System Controllers
Advanced non linear
Digital twins
Action
=
c
State
=
Measurement
Reward
=
-
F_c(m)
Action
=
pv_av
State
=
(vs,vs’,setpoint)
Reward
=
-
(vs-setpoint)
Action
=
pedalVector
State
=
SeepLimitCurve
Reward
=
-
8. SAE INTERNATIONAL
Non linear optimizers – Fmincon (Automated Calibration)
Model predictive control - Speed advisor
Paper # (if applicable) 8
Goal :
The idea is to suggest energy optimal vehicle speed
trajectories with constraints on vehicle dynamics on the one
hand and the upcoming speed limits on the other.
Solution Space:
Data Generation: The synthetic data for training the MPC is
generated via non linear optimizer.
Optimiser:
VSn+1 = f (pedal value, envn cdn, VSn )
Subject to constraints
f (pedal value, envn cdn, VSn ) < Speed limits
Pedal value min < predicted pedal value < Pedal value max
Vehicle Model
(Plant)
Vs
Environment
Recommendations
9. SAE INTERNATIONAL
Non linear optimizers - Fmincon
Model predictive control - Speed advisor
Paper # (if applicable) 9
AI is not used directly
Non Linear optimizers -> fmincon
Ant colony Optimization
Particle swam optimization
Goal : To find the global minimum for a constrained
nonlinear multivariable function
Hybridization of algorithm
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How to model missing control Bio Inspired Computing
Paper # (if applicable) 10
Adaptive Hill Climbing
PSO
ANT colony optimisation
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Deep Reinforcement Learning - System, Controllers
Mathematical Model
Paper # (if applicable) 11
Goal :
To predict post injected fuel quantity for reaching the
temperature setpoint.
Solution Space:
Observations = f(current temperature, error, integral error)
Reward = MSE < Threshold → Positive Reward
MSE > Threshold → Negative Reward
MSE Grad > 0 → Negative Reward
MSE Grad < 0 → Positive Reward
Stop Creterion = Min T > current T
• Max T < current T
• MSE < Threshold
• Action > Threshold
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What we do
Paper # (if applicable) 12
RL usually used in gaming
GO and chess are best examples
Typical fuel systems are stochastic processes
RL used as
Very limited information about the world
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Example for AI based Intellengent BMS
Paper # (if applicable) 13
• Smart battery usage for traveling A to B
• When the charge is less then can go to nearest charging station
• Optimize the battery usage in the route by having better charging and
discharging profile
• Intelligent Battery Management System for various stops in the drive.
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Predictive Battery Management System
Paper # (if applicable) 14
Without Predictive SOC
• No way to check the SOC thresholds
• No way to control the total charging
• SOC at charging not a function of
distance to be travelled.
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Predictive Battery Management System
Paper # (if applicable) 15
SoC Predictor
Time
Current
Voltage
SOC
Distance to
Destination
Decision Engine
(Fuzzy/SVM)
Charging
Station
Driving
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Predictive Battery Management System - SOC Prediction
Paper # (if applicable) 16
Neural Network
Based
SoC Predictor
Time
Current
Voltage
SOC
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Predictive Battery Management System
Paper # (if applicable) 17
Prediction of
Range
(SVM/Fuzzy)
Distance
SOC
Classification
Classification via SVM
Classification via Fuzzy
Based on Classification and visual inspection the
rider can decide on charging station
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Predictive Battery Management System
Paper # (if applicable) 18
With Predictive SOC
• SOC thresholds are monitored always
• Total charging control is based on the
operating conditions
• SOC is a function of distance to be
travelled.
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Conclusion
Paper # (if applicable) 19
Accurate faster models for embedded system
Fast transient response can always be achieved by having
encapsulation of numerical methods and AI
AI can be effectively used to model missing physics during
transients
Usage of AI in all stages of development improves the
accuracy and performance.
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References
Paper # (if applicable) 20
1. Orchestrating Infrastructure for sustainable Smart Cities: http://www.iec.ch/
whitepaper/pdf /iecWP-smartcities-LR-en.pdf
2. Rohith Kamath, Vivek Venkobarao, “RT nonlinear models and model reduction
techniques for engine management systems - airpath dynamics”, FISITA
World Automotive Congress 2018, F2018/F2018-PTE-089
3. Rohit Kamath, Vivek Venkobarao, Prof Subramaniam, Simulation and Design
of Decentralized PI Observer Based Controller for Nonlinear Interconnected
Systems of the Diesel Engine Airpath DOI 10.1016/j.egypro.2017.05.103
4.Rohit Kamath, Vivek Venkobarao, Prof Subramaniam, “An analytical model of
diesel engine intake system for performance prediction”, CMC congress pune
May 10 2016
5.2008E19407 IN Vivek Venkobarao - Hybridizing Genetic Algorithms with
simulated annealing and Dynamic adaptive methods for global optimization –
Patent Application published