• Energy Research

As chlorate concentrations have been found to be harmful to human and animal health, governments are increasingly demanding strict control of the chlorate concentration in drinking water. Since there are no chlorate sensors available, the current solution is sampling and laboratory analysis. This is costly and time consuming. The aim of this work was to investigate Sensor Data Fusion (SDF) as an alternative approach, with a focus on chlorate formation in the electrochlorination process, and design an observer for the real-time estimation of chlorate. The pH, temperature and UV-a absorption were measured in real time. A reduced-order nonlinear model was derived, and it was found to be detectable. An Extended Kalman Filter (EKF), based on this model, was then used to estimate the chlorate formation. The EKF algorithm was verified experimentally and was found to be capable of accurately estimating chlorate concentrations in real time. Electrochlorination is an emerging and efficient method of disinfecting drinking water. Soft sensing of chlorate concentrations, as proposed in this paper, may help to better control and manage the process of electrochlorination.

Sensor Data Fusion (SDF) is a widely used means of monitoring electrochemical processes. The application of SDF contributes to solving challenges in process efficiency, control and reliability. Due to recent, stringent regulations, there is a need to monitor the formation of by-products in electrochlorination, such as chlorate. For this development, the knowledge of SDF produced in neighboring fields of research, such as on batteries or fuel cells, can be of great value. This paper presents an overview of the application of SDF algorithms to monitor electrochemical processes, and discusses how to best apply SDF to monitor by-product concentrations in the context of electrochlorination. Both first-principles and data-driven approaches are discussed. Successful application of SDF to electrochlorination monitoring will improve the safety of drinking water supply. In addition, this overview can inspire and improve the application of SDF in the monitoring of other electrochemical systems.