Modeling electric Vehicle's and improving battery lifetime using AI tools case study: Postal cars.

The rapid development in the field of electric vehicles requires a careful evaluation of the design process. The presence of a simulation model of the electric vehicle can effectively detect many faulty areas during the development process without risks. The MATLAB and Simulink environment is considered one of the most important tools used in the simulation process. In this paper, we will present the model of electric car used for transporting postal parcels (postal cars). The model includes simulating the operation of a permanent magnet synchronous electric motor. We will assume that the car is moving according to a driving cycle. The results will show the torque forces required to achieve the required speed. We will further calculate the traction and the resistance forces during the driving cycle and the engine efficiency in addition. Perhaps the most important problem facing electric car designers is calculating the amount of energy consumed from the battery or hydrogen fuel, and this is what was achieved as the result of the simulation process in this research. In the end, use one of the artificial intelligence tools (fuzzy controller) to improve battery life by providing the electric car driver with an alert system that will increase the ability to monitor the battery condition and thus increase battery life. The benefit of this paper emerges in realizing the importance of modeling and using simulation using artificial intelligence in developing the design of the electric car, specially the electric motor and battery size, and thus achieving one of the most important goals of the United Nations of preserving the environment and reducing carbon emissions.

Data from long time testing of 18650 lithium polymer batteries.

This is a data set from long time testing of 18650 Lithium polymer batteries. It includes the following batteries: Samsung ICR18650-30B (2950 mAh), Joy NCR18650A300A (3000 mAh), GP 03624RC 3.6 V (3000 mAh) and EVC 200L06C (2000 mAh). For measurement, four batteries are connected in parallel and are charged and discharged with a controlled current of 1 A per battery. The current is controlled with a NI cRIO control system programmed in LabView. Battery current is measured with LEM LA 55-P current transducers; voltage is measured directly with the cRIO's analog inputs. The data set contains measurement for between 1200 and 1940 full charging/discharging cycles. The data set can be reused to get information about the dependence of battery capacity vs. number of cycles. Temperature of the battery is measured, therefore the dependence of capacity on temperature can be found out as well.

Linear and nonlinear optical susceptibilities and the hyperpolarizability of borate LiBaB9O15 single-crystal: theory and experiment.

The single-crystal borate LiBaB9O15 was synthesized by a high-temperature solution reaction and structurally determined by the single-crystal X-ray diffraction technique. It crystallizes in the noncentrosymmetric space group R3c and features a three-dimensional ∞3[B9O15]3­ anionic framework, with infinite channels in which the Li+ and Ba2+ cations are located. The linear optical properties were investigated experimentally in terms of the absorption spectrum, which reveals an optical gap of 5.17 eV. In addition we have calculated the linear optical properties using state-of-the-art all-electron full potential linearized augmented plane wave method. The nonlinear optical susceptibilities, namely, the second harmonic generation and the hyperpolarizability of the single-crystal borate LiBaB9O15 are calculated and evaluated at a static limit and at λ = 1064 nm. The calculation shows there exists three second-order nonlinear optical susceptiblities tensors components. We present measurements of the IR spectra in the range 500­2000 cm­1, and the second harmonic generation was performed using a Quantel 15 ns Nd:YAG laser operating at 1064 nm.