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Automotive air conditioning (ACC) system designers faced unique challenges in satisfying customer demands for efficient and comfortable operation across a broad temperature range. The AAC system's effective or fixed temperature setting makes this possible. Many climate control models, like the state flow switching controller in MATLAB control, must handle heating and cooling due to a single Simulink/environment software and frequently contain steady-state error (SSE). The present research proposes to design an automatic temperature control scheme and fuzzy logic control (FLC) for an automotive air-conditioned (AAC) system. In addition, it employs MATLAB Simulink/environment software to model the fuzzy control technique to analyze the AAC system's response. A simulation has been set up to evaluate the suggested system performance to match a selection of user-specified reference temperatures and compressor speeds. Compared with a PID-controlled AAC system, the proposed FLC-based system reduced the undershoot to only 2.30% from 33.30% respectively, and was robust, quicker, and better at controlling temperature. • Challenges in automotive air conditioning systems for designers were addressed. • An automatic temperature control scheme was proposed via fuzzy logic control. • Improved efficiency and comfort in the AAC system was achieved. • The proposed FLC-based system reduced the undershoot to 2.30% from 33.30%. • The FLC-based was more robust, quicker, and better at controlling temperature. [ABSTRACT FROM AUTHOR]

This paper aims to design thermal dummy cells (TDCs) that can be used in the development of lithium-ion battery thermal management systems. Based on physical property and geometry of real 18,650 cylindrical cells, a three-dimensional model of TDCs was designed, and it is used to numerically simulate the thermal performance of TDCs. Simulations show that the TDC can mimic the temperature change on the surface of a real cell both at static and dynamic current load. Experimental results show that the rate of heating resistance of TDC is less than 0.43% for temperatures between 27.5 °C and 90.5 °C. Powered by a two-step voltage source of 12 V, the temperature difference of TDCs is 1 °C and 1.6 °C along the circumference and the axial directions, respectively. Powered by a constant voltage source of 6 V, the temperature rising rates on the surface and in the core are higher than 1.9 °C/min. Afterwards, the proposed TDC was used to simulate a real cell for investigating its thermal performance under the New European Driving Cycle (NEDC), and the same tests were conducted using real cells. The test indicates that the TDC surface temperature matches well with that of the real battery during the NEDC test, while the temperature rise of TDC exceeds that of the real battery during the suburban cycle. This paper demonstrates the feasibility of using TDCs to replace real cells, which can greatly improve safety and efficiency for the development of lithium-ion battery thermal management systems. [ABSTRACT FROM AUTHOR]

In remote measurement systems, the lead wire resistance of the resistance sensor will produce a large measurement error. In order to ensure the accuracy of remote measurement, a novel lead-wire-resistance compensation technique is proposed, which is suitable for a two-wire resistance temperature detector. By connecting a zener diode in parallel with the resistance temperature detector (RTD) and an interface circuit specially designed for it, the lead-wire-resistance value can be accurately measured by virtue of the constant voltage characteristic of the zener diode when reverse breakdown occurs, and compensation can thereby be made when calculating the resistance of RTD. Through simulation verification and practical circuit testing, when the sensor resistance is in 848–2120 Ω scope and the lead wire resistance is less than 50 Ω, the proposed technology can ensure the measuring error of the sensor resistance within ±1 Ω and the temperature measurement error within ±0.3 °C for RTDs performing 1000 Ω at 0 °C. Therefore, this method is able to accurately compensate the measurement error caused by the lead wire resistance in two-wire RTDsand is suitable for most applications. [ABSTRACT FROM AUTHOR]

The optimal power flow problem is one of the most widely used problems in power system optimizations, which are multi-modal, non-linear, and constrained optimization problems. Effective constrained optimization methods can be considered in tackling the optimal power flow problems. In this paper, an ϵ -constrained method-based adaptive differential evolution is proposed to solve the optimal power flow problems. The ϵ -constrained method is improved to tackle the constraints, and a p-best selection method based on the constraint violation is implemented in the adaptive differential evolution. The single and multi-objective optimal power flow problems on the IEEE 30-bus test system are used to verify the effectiveness of the proposed and improved ε adaptive differential evolution algorithm. The comparison between state-of-the-art algorithms illustrate the effectiveness of the proposed and improved ε adaptive differential evolution algorithm. The proposed algorithm demonstrates improvements in nine out of ten cases. [ABSTRACT FROM AUTHOR]

Abstract: Hydrogen fuel is regarded as one of the most promising alternative fuels for automobiles in future. Technology of the optimum control on hydrogen-fueled engines is a key to improve its performances in every respect. In this paper, based on the experiments, the policy of optimum control on hydrogen-fueled engines has been shown. Moreover, a new optimizing control model on hydrogen-fueled engines has been constructed, in which ignition timing, injection timing and injection duration were separately selected as control variation, and output power and rate of fuel consumption are separately chosen as performance index function. Further, a new method ingeniously adopting fuzzy-neural network (FNN) system to calculate the optimizing control laws for the optimizing control model has been designed, and a series connection control system has been set up, which is composed of FNN controllers combined with an adaptive controller for ignition timing to realize open-loop or closed-loop control pattern with stepping regulation of ignition timing. Last, the calculated results of the control variations with an improved FNN system were contrasted with experimental results; the contrasting result has shown that the maximum absolute error is less than 1°CA, the maximum relative error is less than 5%, mean square error is 0.381°CA. Therefore, the calculation method with FNN system is practical and satisfactory. [Copyright &y& Elsevier]