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Accurately predicting the state of charge (SOC) and state of health (SOH) of lithium iron phosphate batteries is crucial for the safe operation of electric vehicle battery systems. However, the Unscented Kalman Filter (UKF) algorithm, commonly used for battery state estimation, exhibits significant errors under low-temperature conditions due to changes in ion mobility and increased internal resistance. To address this, a UKF algorithm incorporating a temperature compensation model is proposed. First, a SOC-OCV functional relationship is established through analysis of experimental data, achieving a high fitting degree of 0.999. Then, a temperature compensation model is integrated to refine the UKF estimation by accounting for the increased electrolyte viscosity and reduced reaction kinetics at low temperatures. Simulation results demonstrate that the proposed UKF with temperature compensation exhibits lower mean squared errors in SOC and SOH estimation, ensuring robust and accurate performance, even as ambient temperatures decrease.

Most of the conventional pH measurements were carried out in acidic to slightly alkaline solutions. In this pH range, the effect of temperature during the measurement is negligible and can be ignored. However, the pH value for highly alkaline solutions is considerably sensitive to their temperature change. A slight difference in temperature can affect the accuracy of the pH test result. Cement‐based materials (CBMs) are highly alkaline. The influence of temperature shall be minimised to compare the pH values of different CBMs precisely. In the literature related to pH measurement for CBMs, the solution temperature during the pH measurement was not recorded, whilst the room temperature recorded was in the range of 20°C–30°C. Therefore, solution temperature compensation (STC) shall be introduced into the pH measurement for CBMs to convert the measured pH into the pH value at a reference temperature of 25°C. To this end, firstly, the pH–temperature profile of the solutions was generated to identify the STC factor ( f STC , also known as solution temperature coefficient). Then, the solution temperature‐compensated pH (pH STC ) was calculated using f STC to present the pH value in the reference temperature of 25°C. However, no standardised method exists for the generation of this pH–temperature profile. In this study, a simple method for generating pH–temperature profile and calculating pH STC for CBMs was introduced.

Resistance errors in bandgap reference (BGR) circuits often cause deviations in design indicators, and it is true that utilizing various compensation techniques mitigates the impact of resistance errors. In this paper, an original BGR circuit with 180 nm BCD processing is presented, which uses an improved high-order compensation and curvature compensation. The proposed BGR contains four main blocks, including a start-up stage, a first-order temperature compensation stage, a high-order temperature compensation stage, and a curvature compensation stage. Meanwhile, a trimming resistor array structure is designed to revise the temperature coefficient (TC) deviation of the test output voltage from the theoretical design value. Through wafer-level laser trimming technology, the measurement results are achieved with very little difference from the theoretical design value. The proposed BGR provides a stable reference voltage at 1.25 V with a low TC and strong power supply rejection (PSR). Within temperatures ranging from −45 °C to 125 °C, the measured TC shows an optimal value at 4.2 ppm/°C and the measured PSR shows −100 dB.

Damage detection is one of the great challenges of the maintenance tasks and it has involved numerous researches to develop techniques in the field of structural health monitoring (SHM). Among different techniques, electromechanical impedance (EMI) technique has attracted attention due to its important and promising results. However, the sensitivity of this technique to variations in environmental conditions can lead to false diagnoses, and the temperature is one of the most critical factors for EMI technique. In view of this point, different researchers have developed compensation techniques to minimize the effects caused by temperature variation in electromechanical impedance measurements. Another important issue related to electromechanical Impedance curves is about the frequency range chosen to be analyzed. Then, the present article introduces an improved approach for damage detection by adding a new step for the temperature compensation technique proposed in a well-established approach in the literature. The proposal comprises a strategy to select the frequency range to compute damage detection indexes, and the technique is demonstrated for an aluminum beam in three different structural conditions: corresponding to the healthy and two types of damaged structure. The results are investigated for four different frequency ranges. The findings demonstrate the effectiveness of the proposed approach to reduce false alarms in damage detection using the EMI technique.

Tunnel magnetoresistance (TMR) sensors, known for their high sensitivity, efficiency, and compact size, are ideal for detecting weak currents, particularly leakage currents in smart grids. However, temperature variations can negatively impact their accuracy. This work investigates the effects of temperature variations on measurement accuracy. We analyzed the operating principles and temperature characteristics of TMR sensors and proposed a high-precision, software-based temperature compensation method using cubic spline interpolation combined with polynomial regression and zero-point self-calibration. Additionally, a field-programmable gate array (FPGA)-based temperature compensation circuit was designed and implemented. An experimental platform was established to comprehensively evaluate the sensor’s performance under various temperature conditions. Experimental results demonstrate that this method significantly enhances the sensor’s temperature stability, reduces the sensitivity temperature drift coefficient, and improves zero-point drift stability, outperforming other compensation methods. After compensation, the sensor’s measurement accuracy in complex temperature environments is substantially improved, enabling effective weak current detection in smart grids across diverse environments.

An MEMS resonant accelerometer is a temperature-sensitive device because temperature change affects the intrinsic resonant frequency of the inner silicon beam. Most classic temperature compensation methods, such as algorithm modeling and structure design, have large errors under rapid temperature changing due to the hysteresis of the temperature response of the accelerometer. To address this issue, we propose a novel reservoir computing (RC) structure based on a nonlinear silicon resonator, which is specifically improved for predicting dynamic information that is referred to as the input–output-improved reservoir computing (IOI-RC) algorithm. It combines the polynomial fitting with the RC on the input data mapping ensuring that the system always resides in the rich nonlinear state. Meanwhile, the output layer is also optimized by vector concatenation operation for higher memory capacity. Therefore, the new system has better performance in dynamic temperature compensation. In addition, the method is real-time, with easy hardware implementation that can be integrated with MEMS sensors. The experiment’s result showed a 93% improvement in IOI-RC compared to raw data in a temperature range of −20–60 °C. The study confirmed the feasibility of RC in realizing dynamic temperature compensation precisely, which provides a potential real-time online temperature compensation method and a sensor system with edge computing.

Thermoelectric pile, which uses non-contact infrared temperature measurement principle, is widely used in various precision temperature measuring instruments. This paper analyzes environmental temperature's influence on thermoelectric piles' measurement accuracy and proposes a environment temperature compensation based on GA-BP (Genetic Algorithm-Back Propagation) neural network. The GA algorithm makes up for the slow iterative speed and easy to fall into local optimization of BP algorithm. The experimental simulation results show that environment temperature compensation based on GA-BP can accurately correct the measurement error caused by environmental temperature and other factors.

Resonant pressure microsensors are widely used in the fields of aerospace exploration and atmospheric pressure monitoring due to their advantages of quasi-digital output and long-term stability, which, however, requires the use of additional temperature sensors for temperature compensation. This paper presents a resonant pressure microsensor capable of self-temperature compensation without the need for additional temperature sensors. Two doubly-clamped “H” type resonant beams were arranged on the pressure diaphragm, which functions as a differential output in response to pressure changes. Based on calibration of a group of intrinsic resonant frequencies at different pressure and temperature values, the functions with inputs of two resonant frequencies and outputs of temperature and pressure under measurement were obtained and thus the disturbance of temperature variations on resonant frequency shifts was properly addressed. Before compensation, the maximal errors of the measured pressure values were over 1.5% while after compensation, the errors were less than 0.01% of the full pressure scale (temperature range of −40 °C to 70 °C and pressure range of 50 kPa to 110 kPa).

In this study, we propose a microelectromechanical system (MEMS) force sensor for microflow measurements. The sensor is equipped with a flow sensing piezoresistive cantilever and a dummy piezoresistive cantilever, which acts as a temperature reference. Since the dummy cantilever is also in the form of a thin cantilever, the temperature environment of the dummy sensor is almost identical to that of the sensing cantilever. The temperature compensation effect was measured, and the piezoresistive cantilever was combined with a gasket jig to enable the direct implementation of the piezoresistive cantilever in a flow tube. The sensor device stably measured flow rates from 20 μL/s to 400 μL/s in a silicon tube with a 2-mm inner diameter without being disturbed by temperature fluctuations.

This article proposes a novel method for the temperature-compensated inductance-to-frequency converter with a single quartz crystal oscillating in the switching oscillating circuit to achieve better temperature stability of the converter. The novelty of this method lies in the switching-mode converter, the use of additionally connected impedances in parallel to the shunt capacitances of the quartz crystal, and two inductances in series to the quartz crystal. This brings a considerable reduction of the temperature influence of AT-cut crystal frequency change in the temperature range between 10 and 40 °C. The oscillator switching method and the switching impedances connected to the quartz crystal do not only compensate for the crystal’s natural temperature characteristics but also any other influences on the crystal such as ageing as well as from other oscillating circuit elements. In addition, the method also improves frequency sensitivity in inductance measurements. The experimental results show that through high temperature compensation improvement of the quartz crystal characteristics, this switching method theoretically enables a 2 pH resolution. It converts inductance to frequency in the range of 85–100 µH to 2–560 kHz.