Abstract

EBSF_2 is a research project led by the International Association of Public Transport and funded by the"br" European Union with the aim of increasing attractiveness and efficiency of urban bus systems. EBSF_2"br" combines experiments with research as it relies on demonstrators, i.e. innovative technologies are tested on"br" vehicles operating in 12 European bus networks and evaluated through a methodology to assess the soundness of"br" the innovations and their affordability. The innovations under test are different, but increased energy efficiency"br" is the goal for several test sites which are working to: a) advance energy management of buses, b) lower the"br" energy needed for on-board heating, ventilating and cooling; c) develop energy-efficient driver support systems."br" The paper describes how the topic energy efficiency is addressed within the EBSF_2 demonstrators. The"br" assessment methodology designed to measure the performance variations in each demonstrator and cross-case is"br" presented, together with the testing scenarios for three demonstrators and the preliminary results achieved.

Abstract

Typically, the unique objective pursued in either active or passive balancing is equalization of single cell charge. However, a balancing circuit may offer more control features, like virtual equalization of single cell internal resistance or thermal balancing. Such control features for balancing systems are evaluated in this paper by means of convex optimization. More than one hundred cases in a pure EV application are evaluated. Balancing circuits' efficiency models are implemented and realistic cell-to-cell parameter distributions are considered based on experimental data. Different battery sizes and driving cycles are considered. Balancing circuit topology is taken into account by selecting a specific category of energy transfer: cell-to-heat, bypass, cell-to-pack, pack-to-cell, cell-to-cell shared, cell-to-cell distributed or cell-to-pack-to-cell. In general, better results in terms of energy losses, available capacity or temperature are obtained for the last three categories, even for moderate balancing currents. In particular, remarkable improvements are observed under conditions of high power demand with high variability, i.e., smaller battery sizes and more demanding driving cycles.

Abstract

Battery thermal management is essential to efficienct and safe operation of Li-ion batteries, particularly in challenging applications such as fast charging. This work proposes a thermal management control framework based on MPC. The novelty of this approach resides in the focus on incorporating disturbance prediction into the control decision. Simulations show that this methodology allows for (1) lower peak and mean battery temperatures during fast charging for a similarly sized battery thermal management system; or (2) battery thermal management system downsizing for similar thermal performance.