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Developing and Improving Hardware and Firmware of a Smart Device Able to Perform an Accurate Diagnosis of Lead-Acid Batteries for Automotive Applications

Servan Tursak

Developing and Improving Hardware and Firmware of a Smart Device Able to Perform an Accurate Diagnosis of Lead-Acid Batteries for Automotive Applications.

Rel. Marcello Chiaberge. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2021

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ABSTRACT Since nowadays, especially in the automotive field, lead-acid batteries are getting more important, a good diagnostic of the batteries is becoming essential. The aim of this thesis work is to develop and improve the hardware and the firmware designs of a smart device that is developed before as a research prototype. The whole purpose of this thesis work is to acquire the necessary parameters, such as voltage, current, temperature, etc. in order to calculate an accurate estimation of SoC (State of Charge) and SoH (State of Health) and send them to a smart central device through Bluetooth using BLE (Bluetooth Low Energy) protocol. The voltage of the terminals of the battery is measured using a negative feedback amplifier after using a proper voltage divider to have a proper voltage range for the operational amplifier itself. The analog value is acquired through the analog pins of the microcontroller utilizing its own ADC (Analog to Digital Converter). The current of the battery is also measured by using a Shunt Resistor of 50 micro ohms. For this purpose, the idea is basically first to measure the voltage drop across the terminals of the shunt resistor and then convert it to the current by a firmware algorithm. In order to measure the voltage difference across the shunt resistance, a differential amplifier is utilized since it has a simple design and good gain efficiency. After using the differential amplifier and after amplifying the voltage drop, the data is fed to the analog pins and ADC of the microcontroller. After having the necessary parameters acquired, they need to be sent to a smart device by using the BLE protocol. For this purpose, application-specific Service and Characteristic creations were necessary. Using an online tool developed by Texas Instruments, some pieces of code are generated and embedded inside the firmware of the design. At that point, the acquired parameters are sent to the central Bluetooth device and monitored by checking the specific area of the created Service and Characteristics. Since the company has decided not to build the hardware design due to Covid and economical situations, the related firmware is tested on a Launchpad that has exactly the same microcontroller and the required drivers, such as timer and ADC. After flashing the firmware onto the Launchpad, the results on the smart device screen are checked by using the BLE Scanner application. the voltage and the current values are tested at the minimum and maximum points and the results were satisfactory. For future development, since the hardware design includes a flash memory inside, the offline measuring can be applied. That would be very useful when considering that not always have a Bluetooth connection. The results can be stored inside the flash memory and then once the user connects the device to Bluetooth, the acquired results can be monitored then. Also as an important point, Cloud Computing can be considered for this thesis work. Since it allows us to connect many devices from many different users, it will make the estimations of the SoC and SoH much accurate. This thesis work has a big potential to serve as a real industrial solution since it is a complete project with both hardware and firmware designs. Especially when considering that we are in a transition phase from fuel vehicles to electric vehicles, this work can be well utilized for battery diagnostics which will be crucial in the future more than it is now.

Relators: Marcello Chiaberge
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 114
Corso di laurea: Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering)
Classe di laurea: New organization > Master science > LM-29 - ELECTRONIC ENGINEERING
Aziende collaboratrici: Brain technologies
URI: http://webthesis.biblio.polito.it/id/eprint/17911
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