Surrogate Model of the Optimum Global Battery Pack Thermal Management System Control

_The control of the battery-thermal-management-system (BTMS) is key to prevent catastrophic events and to ensure long lifespans of the batteries. Nonetheless, to achieve a high-quality control of BTMS, several technical challenges must be faced: safe and homogeneous control in a multi element system with just one actuator, limited computational resources, and energy consumption restrictions. To address those challenges and restrictions, we propose a surrogate BTMS control model consisting of a classification machine-learning model that defines the optimum cooling-heating power of the actuator according to several temperature measurements. The la-belled-data required to build the control model is generated from a simulation environment that integrates model-predictivecontrol and linear optimization concepts. As a result, a controller that optimally controls the actuator with multi-input temperature signals in a multi-objective optimization problem is constructed. This paper benchmarks the response of the proposal using different classification machine-learning models and compares them with the responses of a state diagram controller and a PID controller. The results show that the proposed surrogate model has 35% less energy consumption than the evaluated state diagram, and 60% less energy consumption than a traditional PID controller, while dealing with multi-input and multi-objective systems.European Commissio: Grant Agreement No. 824300

Low cost pressure sensors for impact detection in composite structures

AbstractA new technology of flexible pressure sensors is developed using conducting polymers as electroactive materials on plastic substrates. The sensor measures quantitative pressure and the use of an appropriate synthesis strategy in the electroactive material tuning an adequate electrical conductivity and film morphology allows working pressure ranges to be taylor-made designed. Using low cost materials, high surface sensors are easily fabricated. The present work describes the integration of this innovative, low cost and flexible technology on composite structures opening interesting potential opportunities for impact detection and measurements on these types of components

Capacity and Impedance Estimation by Analysing and Modeling in Real Time Incremental Capacity Curves

The estimation of lithium ion capacity fade and impedance rise on real application is always a challenging work due to the associated complexity. This work envisages the study of the battery charging profile indicators (CPI) to estimate battery health indicators (capacity and resistance, BHI), for high energy density lithium-ion batteries. Di erent incremental capacity (IC) parameters of the charging profile will be studied and compared to the battery capacity and resistance, in order to identify the data with the best correlation. In this sense, the constant voltage (CV) step duration, the magnitudes of the IC curve peaks, and the position of these peaks will be studied. Additionally, the behaviour of the IC curve will be modeled to determine if there is any correlation between the IC model parameters and the capacity and resistance. Results show that the developed IC parameter calculation and the correlation strategy are able to evaluate the SOH with less than 1% mean error for capacity and resistance estimation. The algorithm has been implemented on a real battery module and validated on a real platform, emulating heavy duty application conditions. In this preliminary validation, 1% and 3% error has been quantified for capacity and resistance estimation.Funding: This work and the project hifi-elements has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 769935

Tactile Sensors Based on Conductive Polymers

This paper presents results from a selection of tactile sensors that have been designed and fabricated. These sensors are based on a common approach that consists in placing a sheet of piezoresistive material on the top of a set of electrodes. We use a thin film of conductive polymer as the piezoresistive mate¬rial. Specifically, a conductive water-based ink of this polymer is deposited by spin coating on a flexible plastic sheet, giving it a smooth, homogeneous and conducting thin film. The main interest in this procedure is that it is cheap and it allows the fabrication of flexible and low cost tactile sensors. In this work we present results from sensors made using two technologies. Firstly, we have used a flexible Printed Circuit Board (PCB) technology to fabricate the set of electrodes and addressing tracks. The result is a simple, flexible tactile sensor. In addition to these sensors on PCB, we have proposed, designed and fabricated sensors with screen printing technology. In this case, the set of electrodes and addressing tracks are made by printing an ink based on silver nanoparticles. The intense characterization provides us insights into the design of these tactile sensors.This work has been partially funded by the spanish government under contract TEC2006-12376-C02

Contrôle de température de la chambre de refroidissement des nanowalkers

Système de contrôle de température de la plateforme Nanowalker5 -- Système de contrôle de la position d'un minisystème pour applications endovasculaires

Development of the State of Warranty (SOW) for Electric Vehicles

There is an exponential increase in electric vehicles on the road that need a follow up in terms of warranty. The proposed state of warranty (SOW) is a metastate that qualitatively describes the warranty fulfillment level of an electric vehicle. All the relevant warranty information is synthesized in a single merit while maintaining the level of detail through the qualitative substates. The developed SOW is calculated with a rule-based logic of an expert system that evaluates the quantitative value of three substates: the remaining warranty, the remaining health and the remaining useful warranty. The SOW provides a synthesized and user-friendly description of the warranty fulfillment state while providing quantitative detailed information of the most relevant features of each of the different maintenance methodologies

Kalman filter and classical Preisach hysteresis model applied to the state of charge battery estimation

The goal of this work is first to include a hysteresis model in the classical equivalent circuit model (ECM) for a battery system and then to improve the estimation of the state of charge (SoC) by applying the Extended Kalman Filter (EKF). The hysteretic behavior of the open circuit voltage (OCV) is modelled with the classical Preisach model used for magnetic materials. The construction of the Preisach operator is made by means of the Everett function identified from experimental data which only involve the charging curves of the battery. Thus, a significant reduction in the time necessary to obtain the measurements is achieved. The model is assessed with some laboratory experiments performed on a lithium-ion battery and the results show that with this procedure hysteresis is very well reproduced, even when interior loops are present. In addition, the use of the EKF allows us to eliminate the measurements noise and ensure the accuracy of SoC estimation. The high computational efficiency and precision of the method, joined to the limited computational resources needed for the numerical implementation, make it particularly suitable for real-time embedded battery management system (BMS) applications. In addition, the proposed methodology is well-adapted to any battery type, independently of the SoC-OCV profile of the hysteresis cycleThis work has been partially supported by FEDER, Ministerio de Economía, Industria y Competitividad-AEI research project MTM2017-86459-R, by Xunta de Galicia (Spain) research project GI-1563 ED431C 2021/15, by DIUBB through project 2120173 GI/C and by ANID-Chile through FONDECYT grant 1211030 and Centro de Modelamiento Matemático (CMM), ACE210010 and FB210005, BASAL funds for centers of excellence from ANID-Chile.S