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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250520T160000
DTEND;TZID=Asia/Kolkata:20250520T170000
DTSTAMP:20260904T212109
CREATED:20250402T095346Z
LAST-MODIFIED:20250624T064402Z
UID:12115-1747756800-1747760400@oorja.energy
SUMMARY:Data-Driven Approaches to Minimize Battery Testing & Improve Degradation Modeling
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Optimizing Cycle Life Testing: Hybrid (Physics + ML) Modeling Approach for Real-world Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			June 18\, 2025\n\n	\n\n	  @  \n\n\n4:00 pm\n\n		\n\n\n\n	\n	  -  \n\n5:00 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Join us for an insightful joint webinar hosted by oorja and Customized Energy Solutions (CES)\, where we discuss oorja’s advanced hybrid (physics + ML) modeling techniques for optimizing battery cycle life testing requirements\, test protocols\, and getting reliable life predictions according to the real-world use case. Agenda Highlights The Importance and Background of Accelerated Life Testing: Understand the need and background for accelerated life testing\, requirements\, and optimization strategies to streamline testing and ensure rapid yet reliable assessments of battery durability.Validation Cases: Learn from real-world case studies demonstrating the successful implementation and validation of optimized testing protocols. Hybrid Modeling for Cycle Life Prediction: Explore how combining physics-based modeling and machine learning techniques enhances the accuracy and efficiency of cycle life predictions.Design of Experiments (DoE) Test Case Matrix: Learn how to effectively construct extensive DoE matrices to enhance predictive modeling accuracy and reliability.Reserve your spot to gain cutting-edge insights and practical strategies from leading battery experts!  								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									View Recording\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prajakta Sabnis	\n			CEnO\, oorja \n	\n				\n				\n				\n				\n									Prajakta brings extensive expertise in customer success and engagement\, honed over years of experience. She has an M.Tech in Microelectronics from IIT Bombay. At oorja\, she leads customer engagement\, ensuring clients receive exceptional support and value from our solutions.  								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Calvin Raj 	\n			Team Lead\, CES\n	\n				\n				\n				\n				\n									Experienced R&D Services team lead at Customised Energy Solutions with a demonstrated history of working in the energy storage industry. During this time\, he has developed his skills in the energy storage domain by building knowledge in li-ion\, lead acid and sodium-ion technologies\, and experience in research\, product development\, engineering\, design\, testing\, analysis\, data processing\, telemetry and conducting trainings.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Data-Driven Approaches to Minimize Battery Testing & Improve Degradation Modeling	\n\n\n		\n	\n		Accelerate BMS Validation Using Synthetic Data
URL:https://oorja.energy/event/data-driven-approaches-to-minimize-battery-testing-improve-degradation-modeling/
LOCATION:Zoho Webinars
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2025/03/Webinar-Banner-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250424T160000
DTEND;TZID=Asia/Kolkata:20250424T170000
DTSTAMP:20260904T212109
CREATED:20250407T230226Z
LAST-MODIFIED:20250425T074742Z
UID:12138-1745510400-1745514000@oorja.energy
SUMMARY:Accelerating Battery Innovation with oorja: A Smarter Approach to Design & Development
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Optimizing Cycle Life Testing: Hybrid (Physics + ML) Modeling Approach for Real-world Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			June 18\, 2025\n\n	\n\n	  @  \n\n\n4:00 pm\n\n		\n\n\n\n	\n	  -  \n\n5:00 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Join us for an insightful joint webinar hosted by oorja and Customized Energy Solutions (CES)\, where we discuss oorja’s advanced hybrid (physics + ML) modeling techniques for optimizing battery cycle life testing requirements\, test protocols\, and getting reliable life predictions according to the real-world use case. Agenda Highlights The Importance and Background of Accelerated Life Testing: Understand the need and background for accelerated life testing\, requirements\, and optimization strategies to streamline testing and ensure rapid yet reliable assessments of battery durability.Validation Cases: Learn from real-world case studies demonstrating the successful implementation and validation of optimized testing protocols. Hybrid Modeling for Cycle Life Prediction: Explore how combining physics-based modeling and machine learning techniques enhances the accuracy and efficiency of cycle life predictions.Design of Experiments (DoE) Test Case Matrix: Learn how to effectively construct extensive DoE matrices to enhance predictive modeling accuracy and reliability.Reserve your spot to gain cutting-edge insights and practical strategies from leading battery experts!  								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									View Recording\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prajakta Sabnis	\n			CEnO\, oorja \n	\n				\n				\n				\n				\n									Prajakta brings extensive expertise in customer success and engagement\, honed over years of experience. She has an M.Tech in Microelectronics from IIT Bombay. At oorja\, she leads customer engagement\, ensuring clients receive exceptional support and value from our solutions.  								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Calvin Raj 	\n			Team Lead\, CES\n	\n				\n				\n				\n				\n									Experienced R&D Services team lead at Customised Energy Solutions with a demonstrated history of working in the energy storage industry. During this time\, he has developed his skills in the energy storage domain by building knowledge in li-ion\, lead acid and sodium-ion technologies\, and experience in research\, product development\, engineering\, design\, testing\, analysis\, data processing\, telemetry and conducting trainings.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Data-Driven Approaches to Minimize Battery Testing & Improve Degradation Modeling	\n\n\n		\n	\n		Accelerate BMS Validation Using Synthetic Data
URL:https://oorja.energy/event/accelerating-battery-innovation-with-oorja-a-smarter-approach-to-design-development/
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2025/04/Webinar-Banner-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250306T160000
DTEND;TZID=Asia/Kolkata:20250306T170000
DTSTAMP:20260904T212109
CREATED:20250409T105233Z
LAST-MODIFIED:20250409T110115Z
UID:12195-1741276800-1741280400@oorja.energy
SUMMARY:Deciphering Fast Charging Dynamics: Achieving the Optimal Charging Strategy for EVs
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Optimizing Cycle Life Testing: Hybrid (Physics + ML) Modeling Approach for Real-world Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			June 18\, 2025\n\n	\n\n	  @  \n\n\n4:00 pm\n\n		\n\n\n\n	\n	  -  \n\n5:00 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Join us for an insightful joint webinar hosted by oorja and Customized Energy Solutions (CES)\, where we discuss oorja’s advanced hybrid (physics + ML) modeling techniques for optimizing battery cycle life testing requirements\, test protocols\, and getting reliable life predictions according to the real-world use case. Agenda Highlights The Importance and Background of Accelerated Life Testing: Understand the need and background for accelerated life testing\, requirements\, and optimization strategies to streamline testing and ensure rapid yet reliable assessments of battery durability.Validation Cases: Learn from real-world case studies demonstrating the successful implementation and validation of optimized testing protocols. Hybrid Modeling for Cycle Life Prediction: Explore how combining physics-based modeling and machine learning techniques enhances the accuracy and efficiency of cycle life predictions.Design of Experiments (DoE) Test Case Matrix: Learn how to effectively construct extensive DoE matrices to enhance predictive modeling accuracy and reliability.Reserve your spot to gain cutting-edge insights and practical strategies from leading battery experts!  								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									View Recording\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prajakta Sabnis	\n			CEnO\, oorja \n	\n				\n				\n				\n				\n									Prajakta brings extensive expertise in customer success and engagement\, honed over years of experience. She has an M.Tech in Microelectronics from IIT Bombay. At oorja\, she leads customer engagement\, ensuring clients receive exceptional support and value from our solutions.  								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Calvin Raj 	\n			Team Lead\, CES\n	\n				\n				\n				\n				\n									Experienced R&D Services team lead at Customised Energy Solutions with a demonstrated history of working in the energy storage industry. During this time\, he has developed his skills in the energy storage domain by building knowledge in li-ion\, lead acid and sodium-ion technologies\, and experience in research\, product development\, engineering\, design\, testing\, analysis\, data processing\, telemetry and conducting trainings.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Data-Driven Approaches to Minimize Battery Testing & Improve Degradation Modeling	\n\n\n		\n	\n		Accelerate BMS Validation Using Synthetic Data
URL:https://oorja.energy/event/deciphering-fast-charging-dynamics-achieving-the-optimal-charging-strategy-for-evs/
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2025/03/Webinar-Banner.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250123T200000
DTEND;TZID=Asia/Kolkata:20250123T210000
DTSTAMP:20260904T212110
CREATED:20250409T110356Z
LAST-MODIFIED:20250409T112455Z
UID:12200-1737662400-1737666000@oorja.energy
SUMMARY:Identifying the Goldilocks Zone: Perfecting Parameters for Li-ion Battery Modeling
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Optimizing Cycle Life Testing: Hybrid (Physics + ML) Modeling Approach for Real-world Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			June 18\, 2025\n\n	\n\n	  @  \n\n\n4:00 pm\n\n		\n\n\n\n	\n	  -  \n\n5:00 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Join us for an insightful joint webinar hosted by oorja and Customized Energy Solutions (CES)\, where we discuss oorja’s advanced hybrid (physics + ML) modeling techniques for optimizing battery cycle life testing requirements\, test protocols\, and getting reliable life predictions according to the real-world use case. Agenda Highlights The Importance and Background of Accelerated Life Testing: Understand the need and background for accelerated life testing\, requirements\, and optimization strategies to streamline testing and ensure rapid yet reliable assessments of battery durability.Validation Cases: Learn from real-world case studies demonstrating the successful implementation and validation of optimized testing protocols. Hybrid Modeling for Cycle Life Prediction: Explore how combining physics-based modeling and machine learning techniques enhances the accuracy and efficiency of cycle life predictions.Design of Experiments (DoE) Test Case Matrix: Learn how to effectively construct extensive DoE matrices to enhance predictive modeling accuracy and reliability.Reserve your spot to gain cutting-edge insights and practical strategies from leading battery experts!  								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									View Recording\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prajakta Sabnis	\n			CEnO\, oorja \n	\n				\n				\n				\n				\n									Prajakta brings extensive expertise in customer success and engagement\, honed over years of experience. She has an M.Tech in Microelectronics from IIT Bombay. At oorja\, she leads customer engagement\, ensuring clients receive exceptional support and value from our solutions.  								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Calvin Raj 	\n			Team Lead\, CES\n	\n				\n				\n				\n				\n									Experienced R&D Services team lead at Customised Energy Solutions with a demonstrated history of working in the energy storage industry. During this time\, he has developed his skills in the energy storage domain by building knowledge in li-ion\, lead acid and sodium-ion technologies\, and experience in research\, product development\, engineering\, design\, testing\, analysis\, data processing\, telemetry and conducting trainings.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Data-Driven Approaches to Minimize Battery Testing & Improve Degradation Modeling	\n\n\n		\n	\n		Accelerate BMS Validation Using Synthetic Data
URL:https://oorja.energy/event/identifying-the-goldilocks-zone-perfecting-parameters-for-li-ion-battery-modeling/
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2025/03/Webinar-Banner-2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241126T150000
DTEND;TZID=UTC:20241126T150000
DTSTAMP:20260904T212110
CREATED:20250409T023906Z
LAST-MODIFIED:20250409T030003Z
UID:12182-1732633200-1732633200@oorja.energy
SUMMARY:Physics Informed ML to Reduce Accelerated Life Testing for Li-Ion Batteries by 75%
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Optimizing Cycle Life Testing: Hybrid (Physics + ML) Modeling Approach for Real-world Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			June 18\, 2025\n\n	\n\n	  @  \n\n\n4:00 pm\n\n		\n\n\n\n	\n	  -  \n\n5:00 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Join us for an insightful joint webinar hosted by oorja and Customized Energy Solutions (CES)\, where we discuss oorja’s advanced hybrid (physics + ML) modeling techniques for optimizing battery cycle life testing requirements\, test protocols\, and getting reliable life predictions according to the real-world use case. Agenda Highlights The Importance and Background of Accelerated Life Testing: Understand the need and background for accelerated life testing\, requirements\, and optimization strategies to streamline testing and ensure rapid yet reliable assessments of battery durability.Validation Cases: Learn from real-world case studies demonstrating the successful implementation and validation of optimized testing protocols. Hybrid Modeling for Cycle Life Prediction: Explore how combining physics-based modeling and machine learning techniques enhances the accuracy and efficiency of cycle life predictions.Design of Experiments (DoE) Test Case Matrix: Learn how to effectively construct extensive DoE matrices to enhance predictive modeling accuracy and reliability.Reserve your spot to gain cutting-edge insights and practical strategies from leading battery experts!  								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									View Recording\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prajakta Sabnis	\n			CEnO\, oorja \n	\n				\n				\n				\n				\n									Prajakta brings extensive expertise in customer success and engagement\, honed over years of experience. She has an M.Tech in Microelectronics from IIT Bombay. At oorja\, she leads customer engagement\, ensuring clients receive exceptional support and value from our solutions.  								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Calvin Raj 	\n			Team Lead\, CES\n	\n				\n				\n				\n				\n									Experienced R&D Services team lead at Customised Energy Solutions with a demonstrated history of working in the energy storage industry. During this time\, he has developed his skills in the energy storage domain by building knowledge in li-ion\, lead acid and sodium-ion technologies\, and experience in research\, product development\, engineering\, design\, testing\, analysis\, data processing\, telemetry and conducting trainings.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Data-Driven Approaches to Minimize Battery Testing & Improve Degradation Modeling	\n\n\n		\n	\n		Accelerate BMS Validation Using Synthetic Data
URL:https://oorja.energy/event/physics-informed-ml-to-reduce-accelerated-life-testing-for-li-ion-batteries-by-75/
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2024/11/Webinar-Banner-3.png
END:VEVENT
END:VCALENDAR