The motivation to write this paper is a need to contribute to research of methods of defence against intentional attacks on components of hybrid power systems (microgrids) based on renewable energy sources and storage systems. Spatially distributed electrical energy sources and energy storage devices are gradually being developed and installed, but the security protection of microgrids or individual components of a microgrid is not being improved accordingly. A good example is a fleet of EVs in an urban environment connected to a microgrid with low level of security measures in place (or sometimes none). The term security refers to protection against intentional attacks, not protection against accidents and malfunctions (safety). Lithium batteries, as potentially the most dangerous devices in a microgrid system, i.e. the most likely targets of intentional attacks, can be protected by adequate protection of their power converters and BMSs. This paper presents some of the possible intentional attacks on a battery energy storage system in a microgrid, as well as proposed improvements to the protection of communication channels, power converters’ process data logging, and physical protection of battery energy storage systems.

This paper proposes a new method for assessing the state of charge (SoC) and identifying the types of different lithium-ion cells used in the battery systems of light electric vehicles. A particular challenge in the development of this method was the SoC estimation time, as the method is intended for implementation in the control system of a bicycle charging station, where the state of charge must be determined immediately after the bicycle is plugged in in order to start the charging process as quickly as possible according to the appropriate charging algorithm. The method is based on the identification of the transfer function, i.e., the dynamic response of the battery voltage to the current pulse. In the learning phase of this method, a database of reference transfer functions and corresponding SoCs for a specific type of battery cell is created. The transfer functions are described by coefficients determined through the optimization procedure. The algorithm for estimating the unknown battery cell SoCs is based on the comparison of the measured voltage response with the responses of the reference transfer functions from the database created during the learning process to the same current signal. The comparison is made by calculating the integral of the square error (ISE) between the response of the specific reference transfer function and the measured voltage response of the battery cell. Each transfer function corresponds to a specific SoC and cell type. The specific SoC of the unknown battery is determined by quadratic interpolation of the SoC near the reference point with the smallest ISE for each battery type. The cell type detection algorithm is based on the fact that the integral squared error criterion near the actual SoC for the actual cell type changes less than the squared error criterion for any other battery cell type with the same SoC. An algorithm for estimating the SoC and cell type is described and tested on several different cell types. The relative error between the estimated SoC and the actual SoC was used as a measure of the accuracy of the algorithm, where the actual SoC was calculated using the Coulomb counting method.

This paper presents an online high-precision calibration method for on-state voltage measurement of power semiconductors using active temperature control. Unlike other calibration techniques, this method operates continuously during converter operation, enabling monitoring of long-term changes in component characteristics. The method is implemented in a diode-based measurement circuit, selected for its fast response and simplicity. Despite these advantages, diode-based circuits have limited accuracy due to forward voltage variability caused by different junction temperatures of diodes and their manufacturing tolerances. By actively controlling the temperature of a diode, and exploiting the fact that the forward voltage is temperature dependent, this method compensates for the diode forward voltage variations and other sources of measurement errors, such as resistance tolerances and voltage drop across the relay contacts. The resulting high-accuracy voltage measurements are critical for applications like monitoring transistor degradation, precise conduction loss calculation, and determining the dynamic on-resistance of wide-bandgap devices. However, achieving a high common-mode rejection ratio, essential for reliable measurements, remains a challenge for the practical implementation of this method.

In 1992, when Rip van Winkle’s (RvW) cipher was first proposed, the needed infinite public source wasn’t practically available yet, and demands for large buffer memory were too high. Nowadays, with many different satellites orbiting the Earth and transmitting terabytes of digital data daily, its feasible implementations can be worked out. New security-critical systems like unmanned ships and submarines or electrical vehicle (EV) charging stations need to be properly protected, because of danger of possible remote hijacking attacks. Security of present standard encryption methods like AES or RSA has already been disputed. In the wake of constant development and improvements on quantum computers and code-breaking algorithms specifically designed for them, stronger encryption methods need to be devised. This paper presents a method of practical implementation of RvW cipher, with several thousand bits strong symmetric encryption keys regenerated daily. The mathematical simplicity and provable strength of one-time pad (OTP) cipher, combined with simple key generation and synchronization method (with both forward and backward security), using one-way simplex broadcast communication only, will provide much stronger encryption.

Mechanical locks have not been fully replaced by electrical locks and are still being researched and improved, along with advanced electronic methods of attack. Moreover, reading pin lengths by detecting their natural frequencies (lock decoding) to forge copies of a legitimate key can be done quickly using active or passive ultrasonic detectors. One possible method of defence against them is manufacturing lock pins using functionally graded materials (FGMs). A pin’s natural frequency (in the range 100 kHz–1 MHz) and hence its ultrasonic pulse transit/reflection time can be correlated to its length if it is made of a homogeneous material. The idea is to design pins made of functionally graded alloys to achieve equal natural frequencies, but also desired positions of standing wave nodes regardless of pin length. To calculate the composition of the FGM alloy, we must first develop mathematical models of a pin’s vibrations. Two simple and fast mathematical models are first derived from the finite-element model (FEM) of a pin. These models are used in an optimization procedure based on the Nelder–Mead simplex method to calculate optimal profiles of Young’s modulus and density along a pin’s longitudinal axis. A successful optimization procedure for 10 key pin lengths is performed to make a pin-tumbler lock resistant to ultrasonic attacks.

In Section 4 of the original publication