State-of-health estimates of batteries are essential for on-board electric vehicles in order to provide safe, reliable, and cost-effective battery operation. This paper suggests a method to estimate the 10 s discharge resistance, which is an established battery figure-of-merit from laboratory testing, without performing the laboratory test. Instead, a state-of-health estimate of batteries is obtained using data directly from their operational use, e.g. on-board electric vehicles. It is shown that simple dynamical battery models, based on a current input and a voltage output, with model parameters dependent on temperature and state-of-charge, can be derived using AutoRegressive with eXogenous input models, whose order can be adjusted to describe the complex battery behavior. Then the 10 s discharge resistance can be conveniently computed from the identified model parameters. Moreover, the uncertainty of the estimated resistance values is provided by the method. The suggested method is validated with usage data from emulated electric vehicle operation of an automotive lithium- ion battery cell. The resistance values are estimated accurately for a state-of-charge and temperature range spanning typical electric vehicle operating conditions. The identification of the model parameters and the resistance computation are very fast, rendering the method suitable for on-board application.

The industrial lignin used here is a byproduct from Kraft pulp mills, extracted from black liquor. Since lignin is inexpensive, abundant and renewable, its utilization has attracted more and more attention. In this work, lignin was used for the first time as binder material for LiFePO₄ positive and graphite negative electrodes in Li-ion batteries. A procedure for pretreatment of lignin, where low-molecular fractions were removed by leaching, was necessary to obtain good battery performance. The lignin was analyzed for molecular mass distribution and thermal behavior prior to and after the pretreatment. Electrodes containing active material, conductive particles and lignin were cast on metal foils, acting as current collectors and characterized using scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS) and galvanostatic charge-discharge cycles. Good reversible capacities were obtained, 148 mAh·g⁻¹ for the positive electrode and 305 mAh·g⁻¹ for the negative electrode. Fairly good rate capabilities were found for both the positive electrode with 117 mAh·g⁻¹ and the negative electrode with 160 mAh·g⁻¹ at 1C. Low ohmic resistance also indicated good binder functionality. The results show that lignin is a promising candidate as binder material for electrodes in eco-friendly Li-ion batteries.

Lifetime testing of batteries for hybrid-electrical vehicles (HEV) is usually performed in the lab, either at the cell, module or battery pack level. Complementary field tests of battery packs in vehicles are also often performed. There are, however, difficulties related to field testing of battery-packs. Some examples are cost issues and the complexity of continuously collecting battery performance data, such as capacity fade and impedance increase. In this paper, a novel field test equipment designed primarily for lithium-ion battery cell testing is presented. This equipment is intended to be used on conventional vehicles, not hybrid vehicles, as a cheaper and faster field testing method for batteries, compared to full scale HEV testing. The equipment emulates an HEV environment for the tested battery cell by using real time vehicle sensor information and the existing starter battery as load and source. In addition to the emulated battery cycling, periodical capacity and pulse testing capability are implemented as well. This paper begins with presenting some background information about hybrid electrical vehicles and describing the limitations with today’s HEV battery testing. Furthermore, the functionality of the test equipment is described in detail and, finally, results from verification of the equipment are presented and discussed.