Radoslav Cipin

Efficient thermal management of electric traction machines is increasingly important as higher power density and reliability requirements push winding temperatures close to their limits, particularly in the end-winding region. However, fast design-oriented procedures linking parametric hairpin winding geometry to simplified winding-temperature estimation and finite element verification remain limited. This paper presents an automated workflow for generating a parametric hairpin end-winding model, combined with an analytical method for estimating the current density for a known heat-transfer coefficient on the end-winding surface. A finite-element thermal model of the same geometry is then developed for comparison. Parametric analyses are performed using both approaches, including an assessment of the sensitivity to the assumed heat-transfer coefficient and the results are presented as parametric sensitivity plots suitable for preliminary design assessment. The proposed method enables rapid preliminary assessment of parametric trends and direct comparison between analytical and finite-element thermal predictions.

This paper deals with the estimation of depth of discharge for Li-ion batteries. Estimation is based on the knowledge of discharging curves measured for discrete values of loading currents. The estimator of the depth of discharge is a form of feedforward neural network which is trained with the measured data of discharge curves. Accuracy of estimation of the depth of discharge is shown for arbitrary generated and measured loading characteristics, where the depth of discharge is estimated by the designed neural network and measured by using the Coulomb counting method.

The paper deals with a thermal model of a battery pack made of a phase-change material. The model is based on the finite element method and is created in the Ansys software. The performed simulations with different discharge cycles indicate that maximum temperatures are lower compared to a battery pack made of an ordinary material without a possibility of phase change.

This paper deals with a mathematical description of an alkaline battery impedance dependence on frequency. This mathematical description is done in two different ways. In the first case, a general fractional transfer function is used and in the second case an artificial neural network is used. Both approaches are discussed and compared with real measurement.

This paper deals with problems with the estimation of the state of charge of Li-ion batteries. There are shown and discussed two basic methods for estimation of the state of charge. There are discussed essential problems with an estimation based on the so-called Coulomb counting method and based on an equivalent circuit of Li-ion battery.

The paper describe design of battery powered drive unit intended for tree harvester application. Battery powered hybrid drive unit in working machine is currently quite common (1). The battery capacitance is not sufficient to realize harvester as an only battery powered machine. Nevertheless, the hybrid concept of electric drive is useful to cover short power peaks demands during the harvester standard operation. In harvester application there is typical high ratio between short power peak and average demanded power. The development in batteries increases of significance and possibility of electric drive utilization in three harvesters.

This paper describes a thermal model of a cylindrical battery cell usable for calculation of instantaneous temperature distribution during discharging. The thermal model is based on a thermal network considering the thermal capacity. The functionality of the model was verified by simulation using the finite element method and a very good coincidence was achieved.

This paper deals with a measurement of alkaline and Li-ion battery impedances in wide-range frequency from about one Hz to a few hundred kHz. Measured battery admittances are used for the construction of battery transfer functions, i.e., the dependences of admittance on frequency. Comparison of transfer functions for different battery types is shown. It is shown that transfer functions for both types have the same form and this transfer function is only the third-order.