No abstract

No abstract

Diesel engines have evolved in order to meet stringent emission standards and to satisfy consumer demand for better fuel efficiency and increased power. The common-rail injection system was introduced in order to satisfy stringent emission standards, low fuel consumption, and low noise in recent years. The performance of a fuel injection system is strongly influenced by the injector characteristics. In this study, non-linear mathematical models are proposed for solenoid-operated and piezo-actuated injectors for control applications. Based on these models, the injection rate, which is one of the most important factors for the injection characteristics, is estimated using a sliding-mode observer. The simulation results and the experimental data show that the proposed sliding-mode observers can effectively estimate the injection timing and the injection rate for both types of common-rail injector.

No abstract

Accurate state of health (SoH) estimation of rechargeable batteries is important for the safe and reliable operation of electric vehicles (eVs), smart phones, and other battery operated systems. We propose a novel method for accurate SoH estimation which does not necessarily need full charging data. Using only partial charging data during normal usage, 10 derived voltage values (v sei) are collected. the initial v sei point is fixed and then for every 1.5% increase in the Coulomb counting, other points are selected. The difference between the v sei values (Δv sei) and the average temperature during the charging form the feature vector at different SOH levels. The training data set is prepared by extrapolating the charging voltage curves for the complete SOH range using initial 400 cycles of data. The trained artificial neural network (Ann) based on the feature vector and SoH values can be used in any battery management system (BMS) with a time complexity of only O n () 4. Less than 1% mean absolute error (MAe) for the test cases has been achieved. the proposed method has a moderate training data requirement and does not need any knowledge of previous SoH, state of charge (Soc) vs. ocV relationship, and absolute Soc value.