Electric vehicle (EV) manufacturers are using cylindrical format cells as part of the vehicle's rechargeable energy storage system (RESS). In a recent study focused at determining the ageing behavior of 2.2 Ah Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 battery cells, significant increases in the ohmic resistance (R O ) were observed post vibration testing. Typically a reduction in capacity was also noted. The vibration was representative of an automotive service life of 100,000 miles of European and North American customer operation. This paper presents a study which defines the effect that the change in electrical properties of vibration aged 18650 NMC cells can have on the control strategy employed by the battery management system (BMS) of a hybrid electric vehicle (HEV). It also proposes various cell balancing strategies to manage these changes in electrical properties. Subsequently this study recommends that EV manufacturers conduct vibration testing as part of their cell selection and development activities so that electrical ageing characteristics associated with road induced vibration phenomena are incorporated to ensure effective BMS and RESS performance throughout the life of the vehicle.

In this paper the detailed procedure of roll speed and roll gap control strategy development for a laboratory scale rolling mill is given. The core of the control strategy is the incorporation of feed-forward compensations based on neural network models for the roll force and roll torque, which are the major disturbances introduced during the rolling operation. An integrated computer simulation model is developed to investigate the performance of the proposed control strategies, and results show significant improvement over the traditional feedback control scheme. Based on the control strategies and the integrated simulation model, a major upgrading scheme is undertaken on an existing laboratory scale rolling mill. The new mill data acquisition and control systems, including the upgrading of the drive and gap motors, are currently under commissioning. After the mill upgrading system is fully commissioned, further work such as online adaptation of the neural network prediction model and the fine-adjustment of the feed-forward compensation need to be investigated for consistent control performance under changing rolling conditions.

Original citation:Bruen, Thomas, Marco, James and Gama, Miguel (2015) Copies of full items can be used for personal research or study, educational, or not-forprofit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. Publisher's statement: A note on versions:The version presented in WRAP is the published version or, version of record, and may be cited as it appears here. Abstract: Battery packs containing multiple cells in series require a balancing system in order to ensure energy and power requirements for the battery pack are maintained throughout its life. Based on the equivalent circuit model (ECM) of a cell, a new framework is proposed which can accommodate a controloriented model of a balancing system while maintaining the same measured input and output as an ECM. This allows for model-based design of the balancing control system and other battery management system functions such as state estimation. Three examples of balancing system models are presented to show how balancing systems can be designed and analyzed. A model-based controller is then designed for one balancing system to show how the framework can be used to generate less heat while removing imbalance at the same rate.

Abstract-an electric vehicle battery pack may employ cells connected electrically in parallel to meet energy and power requirements. For the battery management system, cells connected in parallel are often treated as a single larger component. However, research has identified that the state of charge and cell current may not be equal due to differences in capacity, impedance and cell temperature. In this paper, the authors develop a parallel cell model validated against experimental data. The model is used to evaluate cell energy variation and the impact this can have on the design of highly parallelized battery systems.