Battery Management System Hardware Design for a Student Electric Racing Car

Bat’a, Martin; Mikle, Dávid

doi:10.1016/j.ifacol.2019.12.736

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…The information ecosystem used for college student management includes learning management systems, task management tools, information collection and organization tools, social networks and online communities, and cloud storage services [7][8][9][10][11][12][13][14]. These tools can cooperate and support each other to help college students better manage information and resources, and improve learning and life efficiency [15][16][17][18][19][20][21]. It is helpful to introduce data technology into the college student management informatization ecosystem in better realizing the extraction of student behavior fluctuation information and achieving more targeted student management decisions.…”

Section: Introductionmentioning

confidence: 99%

Construction of College Students’ Management Informatization Ecosystem Based on Data Analysis Technology

Xi¹,

Li²

2023

Int. J. Emerg. Technol. Learn.

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College students’ management informatization ecosystem can help college students better manage information and resources, thus improving learning and life efficiency. It’s important to introduce data technology into the college student management informatization ecosystem, which can better realize the extraction of student behavior fluctuation information and achieve more targeted student management decisions. The current research lacks consideration of its future development trend, such as the impact of the application of technologies, including artificial intelligence, big data Fenix, and the Internet of Things. This paper studies the construction of college students’ management informatization ecosystem based on data analysis technology. Firstly, the design of the data fusion scheme applied to the college students’ management informatization ecosystem is carried out, and the idea of the scheme is given. Aiming at the big data of students’ learning and living behaviors, this paper digs deep into the value of data information, and extract historical student behavior characteristics, providing a basis for short-term student behavior prediction and management decision-making planning and implementation for the college students’ management informatization ecosystem. Based on historical student behavior data and its characteristic data, the XGboost algorithm is used to quantify and extract the importance of each influencing factor on student behavior fluctuations. Experimental results verify the effectiveness of the method proposed in this paper.

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Section: Introductionmentioning

confidence: 99%

Construction of College Students’ Management Informatization Ecosystem Based on Data Analysis Technology

Xi¹,

Li²

2023

Int. J. Emerg. Technol. Learn.

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“…Moreover, there is the need for external systems, such as injectors or compressors, and internal combustion motors require monitoring of fuel and oil parameters, e.g., level, quality, and contamination [ 4 , 5 , 6 , 7 , 8 ]. Thanks to the improvement of DC and AC motor performance, innovative and more efficient power management and storage techniques, and increase in power and energy density of battery packs [ 9 , 10 , 11 , 12 ], many different classes of ground, aerial and underwater vehicles are being designed with a fully electrical powertrain, such as Unmanned Aerial Vehicles (UAV)s [ 13 , 14 , 15 , 16 ], cars [ 17 , 18 , 19 , 20 ], mobile robots in diverse industrial applications [ 21 , 22 , 23 , 24 ] and even short-range aircraft [ 25 ]. Moreover, the extensive use of distributed sensors allows for unprecedented levels of autonomy in mission management and totally novel (and sometimes disruptive) human–machine interfaces.…”

Section: Introductionmentioning

confidence: 99%

Battery Testing and Discharge Model Validation for Electric Unmanned Aerial Vehicles (UAV)

Nisio

Avanzini

Lotano

et al. 2023

Sensors

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Electrical engines are becoming more common than thermal ones. Therefore, there is an increasing interest in the characterization of batteries and in measuring their state of charge, as an overestimation would cause the vehicle to run out of energy and an underestimation means that the vehicle is running in suboptimal conditions. This is of paramount importance for flying vehicles, as their endurance decreases with the increase in weight. This work aims at finding a novel empirical model for the discharge curve of an arbitrary number of battery pack cells, that uses as few tunable parameters as possible and hence is easy to adapt for every single battery pack needed by the operator. A suitable measurement setup for battery tests, which includes voltage and current sensors, has been developed and described. Tests are performed on both constant and variable power loads to investigate different real-world scenarios that are easy to reproduce. The main achievement of this novel model is indeed the ability to predict discharges at variable power based on a preliminary characterization performed at constant power. This leads to the possibility of rapidly tuning the model for each battery with promising accuracy. The results will show that the predicted discharged capacities of the model have a normalized error below 0.7%.

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“…There are various types and safety systems embedded in an electric vehicle. The safety systems in an electric vehicle can include battery system safety [2], braking system safety [3], thermal battery system safety [4], and electrical system safety [5]. Among these various types and safety systems of electric vehicles, electrical system safety is the primary aspect that must be present in an electric vehicle.…”

Section: Introductionmentioning

confidence: 99%

Fault Detection for Low Voltage System in Electric Vehicle

Muhammad Anwar Sadat Faidar,

Kamlasi,

Yusivar

2023

IJECBE

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With the rapid development of the electric vehicle ecosystem, there are concerns about the electrical safety of electric vehicles. This concern is caused by the problems with electric vehicles, which cannot be used when not used for a long time. This problem is caused by a low voltage rating that is not available when the electric vehicle is in that condition. In this study, an algorithm is proposed to support safety for the availability of low-voltage electrical energy, when electric vehicles are in use or not in use. The results of this research indicate that the created algorithm can provide safety for the availability of low voltage level electrical energy, by adjusting the lead-acid battery charging procedure, monitoring the low voltage level while it not in use, and making existing electric vehicles unable to move as long as problems with the low voltage level charging system cannot be resolved.

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Battery Management System Hardware Design for a Student Electric Racing Car

Cited by 3 publications

References 9 publications

Construction of College Students’ Management Informatization Ecosystem Based on Data Analysis Technology

Construction of College Students’ Management Informatization Ecosystem Based on Data Analysis Technology

Battery Testing and Discharge Model Validation for Electric Unmanned Aerial Vehicles (UAV)

Fault Detection for Low Voltage System in Electric Vehicle

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