NB
2021년 8월 12일
As an electrical engineer, I firmly state that this course is the best for anyone who would like to embark on this journey of battery energy storage. Well structured\n\nWith an excellent instructor
BS
2020년 8월 10일
Good and a very challenging course. Really makes you work to understand even the basic concepts. Challenging theoretical and practical assignments. Lot of learning obtained from this course
교육 기관: John W
•2019년 5월 17일
Overall, I good introductory course into Kalman Filtering for SOC estimation. However, the final project was a little bit to easy. In addition to tuning the initial covariance states, maybe add a different part 2 (other than tuning initial parameters) for developing to understand the kalman filter algorithm relating to battery estimation.
교육 기관: Elenchezhiyan M
•2020년 1월 8일
The course was well planned and organised! There is flexibility in the course deadline which is appreciable and suitable for students, Working professionals, faculties.
교육 기관: Vigneshwaran T
•2021년 8월 29일
Don't give up if you are intimidated by the abstract mathematics at the beginning of this course, which is challenging, but after the end of week #2 everything will make sense and the subsequent course content gets much easier. I am a computational chemist and I never even heard of sequential probabilistic inference prior to this course, and I am not that good at mathematics as well. So, believe me Prof. Gregory Plett has done an excellent job on explaining these complicated concepts, turst him and stick with the course until the end. I got everthing I hoped for from this course. I thank Prof. Gregory Plett and Coursera for offering this course.
교육 기관: Albert S
•2020년 3월 2일
This course is comprehensive introduction into the matter. The course explains in detail mathematical concepts behind Kalman filters (and can therefore serve very well for general understanding of estimation theory and Kalman filters), than it shift gently to Kalman filter approaches to state-of-charge. Even with minimum pre-knowledge, after the course ends, one is fully equipped to deal with ECM-based state-of-charges. This course requires dilligent work at home as well. I would recommend it to anyone dealing with battery control algorithms, both at the university, as well as in the private sector.
교육 기관: Davide C
•2020년 5월 1일
This course deeply explains about linear Kalman filter and its non-linear externsion: Estended KF and Sigma Point KF. The course also explains how to apply these powerful tools to battery cells State of Charge estimation, a physical quantity which cannot be measured directly and therefore has to be estimated indirectly based on electrical current, voltage, and temperature. The professor was capable to explain in a simple way such complex mathematics behind Kalman filters theory. I am looking forward to use this new knowledge at work.
교육 기관: Kharan S
•2020년 8월 23일
The course explains the Kalman filter in detail. The highlight of this course is that the professor explains all the complicated mathematics in small advancements that you can easily understand rather than putting a lot in front and confusing a lot.
교육 기관: Nicolas B
•2021년 8월 13일
As an electrical engineer, I firmly state that this course is the best for anyone who would like to embark on this journey of battery energy storage. Well structured
With an excellent instructor
교육 기관: Bhargav S
•2020년 8월 11일
Good and a very challenging course. Really makes you work to understand even the basic concepts. Challenging theoretical and practical assignments. Lot of learning obtained from this course
교육 기관: JustinSmith
•2022년 5월 9일
Using computer models to simulate battery behavior and estimate SOH was a skill I did not have before this course. It was taught in a gradual pace that was comfortable.
교육 기관: Pawel M
•2022년 1월 28일
Excellent course that has very clear teaching material and engaging tests and assignments. A great foundational course for battery algorithms.
교육 기관: Zihao Z
•2022년 1월 18일
Linear Kalman Filter, Extend Kalman Filter, Sigma-point Kalman Filter, very practical, very good course for battery SOC estimation
교육 기관: Ameya K
•2020년 5월 3일
The concepts taught were absolutely crucial for the later parts of this specialization and they were explained properly.
교육 기관: Shovan R S
•2020년 9월 16일
Great course!!! I got hands on experience with all types of kalman filter for battery state estimation.
교육 기관: HAFIZ A A
•2020년 11월 29일
Sir Gregory plett is an excellent Professor Ever and thanks to Coursera for such valuable plateform.
교육 기관: Rodrigo P S
•2022년 2월 24일
Useful to understand Kalman Filters and continue with the Battery Management System specialization.
교육 기관: J S V S K
•2020년 9월 15일
Nice Explanation and programming also easily understandable
교육 기관: Nikhil B
•2020년 7월 10일
A great explanation of SOC estimation using EKF and SPKF.
교육 기관: Piotr M
•2021년 11월 1일
Great knowledge to go deeper into battery world
교육 기관: JAVAID I E
•2022년 4월 6일
It was great to improve the
교육 기관: Nagapoornima S
•2021년 3월 27일
The course was challenging.
교육 기관: 2019BTEEL00034 M S S
•2021년 4월 12일
good course to start upon
교육 기관: Thang N
•2020년 8월 20일
I like this course!
교육 기관: Oscar D S B
•2020년 10월 25일
Excellent course.
교육 기관: VASUPALLI M
•2020년 9월 25일
Excellent course
교육 기관: Ryosuke I
•2020년 10월 9일
とてもいい勉強になりました