Descripción de la oferta
Battery modelling and estimation of certain variables is one of the key aspects to integrate this technology in nowadays applications.
Batteries are nowadays present in many applications such as electric vehicles, electronic portable devices, applications with renewables or medical devices for example.
When a battery is working in these kind of applications some information is required to ensure safety and good performance of the system.
Voltage, current and temperature are typically measured in a battery pack and the battery management system (BMS) takes decisions depending on the values acquired.
However, other non-measurable variables are also estimated nowadays as extra information like state of charge (SOC), state of health (SOH) or state of function (SOF) to have a complete information about the state of the battery during operation.
These estimations have been typically obtained during last years by battery models and are running inside the microprocessor of the BMS.
The type of models used for that purpose are behavioural models based on electrical equivalent circuits or ECM models. These models consist of describing the behaviour of the battery without understanding what is happening inside and they have achieved very good results until now.
There are several research works where ECM models plus some algorithms are used to predict the aforementioned variables successfully.
However, during last years, there is a tendency to model these systems from their physics point of view, trying to represent what is happening inside the battery.
This kind of models are called physics based or electrochemical models and are able to give more information than the regular one obtained with behavioural models, which is considered very interesting to improve current systems.
Physics based models are more complex than behavioural ones and the computational cost is higher but the information obtained at the end can be so useful for a better usage of the battery for any application since the electrochemical processes within the cells are modelled.
There are not many publications about validation of this kind of models with real batteries and this is the topic that the research line wants to study in the PhD work.
During the last six years, the research line has been working on a physics based model for lithium ion batteries that has a very good behaviour but still there are some aspects that can be improved for the future as the assumption of spherical particles in the electrodes, or the assumption of having a non-blended material in the cathode.
Moreover, physics based models are also being considered to help into the design and manufacturing of post lithium battery technologies.
Nowadays, there is a great interest to obtain new battery materials that are able to work for longer times with better specific energy and power behaviours.
Modelling can help to the cathode material designers to know the behaviour of their new material in simulation without the need of making a prototype, thus, reducing the amount of resources used at the end of the process.
To sum up, physics based models for battery systems is considered a tool with great potential for on board and off board applications, but further research is required in this field to be the chosen option in the close future.
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