Lorenz Haghenbeck Emde

Title: Lorenz Haghenbeck Emde: Innovator in Battery Health Estimation

Introduction

Lorenz Haghenbeck Emde is a notable inventor based in Menlo Park, CA (US). He has made significant contributions to the field of battery technology, particularly in estimating the state of health of batteries. His innovative approach combines deep learning techniques with artificial intelligence to enhance battery management systems.

Latest Patents

Emde holds a patent for a "Battery state of health estimator." This invention provides a computing system, method, and apparatus for determining a state of health indication for a battery. A first supervised deep neural network (DNN) is trained using received characteristics for the battery as input and received process parameters as outputs. An unsupervised AI estimator is trained using one or more clustering methods based on extracted features from the first supervised DNN. The received characteristics are input to the unsupervised AI estimator. A second supervised DNN is trained using identified clusters from the unsupervised AI estimator, which are validated with state of health indications. User battery data is then inputted to the second supervised DNN to determine the state of health for the battery. Emde's innovative work in this area is encapsulated in his 1 patent.

Career Highlights

Throughout his career, Emde has worked with prominent companies such as Volkswagen AG and Audi AG. His experience in these organizations has allowed him to apply his expertise in battery technology and contribute to advancements in automotive engineering.

Collaborations

Emde has collaborated with notable professionals in his field, including Melanie Senn and Joerg Christian Wolf. These collaborations have further enriched his work and contributed to the development of innovative solutions in battery health estimation.

Conclusion

Lorenz Haghenbeck Emde is a distinguished inventor whose work in battery state of health estimation showcases the intersection of artificial intelligence and energy technology. His contributions are paving the way for more efficient battery management systems in various applications.