An investigation on the effect of driver style and driving events on energy demand of a PHEV

Environmental concerns, security of fuel supply and CO2 regulations are driving innovation in the automotive industry towards electric and hybrid electric vehicles. The fuel economy and emission performance of hybrid electric vehicles (HEVs) strongly depends on the energy management system (EMS). Prior knowledge of driving information could be used to enhance the performance of a HEV. However, how the necessary information can be obtained to use in EMS optimisation still remains a challenge. In this paper the effect of driver style and driving events like city and highway driving on plug in hybrid electric vehicle (PHEV) energy demand is studied. Using real world driving data from three drivers of very different driver style, a simulation has been exercised for a given route having city and highway driving. Driver style and driving events both affect vehicle energy demand. In both driving events considered, vehicle energy demand is different due to driver styles. The major part of city driving is reactive driving influenced by external factors and driver leading to variation in vehicle speed and hence energy demand. In free highway driving, the driver choice of cruise speed is the only factor affecting vehicle energy demand

Electrochemical modelling of Li-ion battery pack with constant voltage cycling

In a battery pack, cell-to-cell chemical variation, or the variation in operating conditions, can possibly lead to current imbalance which can accelerate pack ageing. In this paper, the Pseudo-TwoDimensional(P2D) porous electrode model is extended to a battery pack layout, to predict the overall behaviour and the cell-to-cell variation under constant voltage charging and discharging. The algorithm used in this model offers the flexibility in extending the layout to any number of cells in a pack, which can be of different capacities, chemical characteristics and physical dimensions. The coupled electrothermal effects such as differential cell ageing, temperature variation, porosity change and their effects on the performance of the pack, can be predicted using this modelling algorithm. The pack charging voltage is found to have an impact on the performance as well as the SEI layer growth. Numerical studies are conducted by keeping the cells at different thermal conditions and the results show the necessity to increase the heat transfer coefficient to cool the pack, compared to single cell. The results show that the thermal imbalance has more impact than the change in inter-connecting resistance on the split current distribution, which accelerates the irreversible porous filling and ageing

A mass transfer based variable porosity model with particle radius change for a Lithium-ion battery

Micro pore-clogging in the electrodes due to SEI growth and other side reactions can cause adverse effects on the performance of a Lithium-ion battery. The fundamental problem of volume fraction variation and particle radius change during the charge-discharge process in a lithium-ion battery is modelled in this paper with the help of mass transfer based formulation and demonstrated on a battery with LiCoO2 chemistry. The model can handle the volume fraction change due to intercalation reaction, solvent reduction side reaction and the electrolyte density change due to side reaction contamination in the battery. The entire calculation presented in this paper models particle radius and volume fraction together and therefore gives greater accuracy in calculating the volume-specific-area of the reacting particles which is an important parameter controlling the Butler-Volmer kinetics. The mass deposit on the electrode (or loss of lithium) gives an indication of the amount of pre-lithiation required to maintain cell performance while the amount of mass deposited on the SEI helps to decide the safe operating condition for which the clogging of pores and capacity fade will be minimal. Moreover the model presented in this paper has wide applicability in analysing the stress development inside the battery due to irreversible porous filling

Structural identifiability of equivalent circuit models for Li-Ion batteries

Structural identifiability is a critical aspect of modelling that has been overlooked in the vast majority of Li-ion battery modelling studies. It considers whether it is possible to obtain a unique solution for the unknown model parameters from experimental data. This is a fundamental prerequisite of the modelling process, especially when the parameters represent physical battery attributes and the proposed model is utilised to estimate them. Numerical estimates for unidentifiable parameters are effectively meaningless since unidentifiable parameters have an infinite number of possible numerical solutions. It is demonstrated that the physical phenomena assignment to a two-RC (resistor–capacitor) network equivalent circuit model (ECM) is not possible without additional information. Established methods to ascertain structural identifiability are applied to 12 ECMs covering the majority of model templates used previously. Seven ECMs are shown not to be uniquely identifiable, reducing the confidence in the accuracy of the parameter values obtained and highlighting the relevance of structural identifiability even for relatively simple models. Suggestions are proposed to make the models identifiable and, therefore, more valuable in battery management system applications. The detailed analyses illustrate the importance of structural identifiability prior to performing parameter estimation experiments, and the algebraic complications encountered even for simple models. View Full-Tex

The influence of temperature and charge-discharge rate on open circuit voltage hysteresis of an LFP Li-ion battery

Open circuit voltage (OCV) is a crucial parameter in an equivalent circuit model (ECM). The path dependence of OCV is a distinctive characteristic of a Li-ion battery; this is known as OCV hysteresis. In this manuscript the influence of temperature and charge/discharge rate on OCV hysteresis has been identified. OCV hysteresis was found to be 13mV higher at 0°C while remaining unchanged at 45°C compared to the 25°C result. In general, OCV hysteresis was found to be less dependent on charge/discharge rate than temperature. The potential explanations of these results have been reported

Modified electrochemical parameter estimation of NCR18650BD battery using implicit finite volume method

The Pseudo Two Dimensional (P2D) porous electrode model is less preferred for real time calculations due to the high computational expense and complexity in obtaining the wide range of electro-chemical parameters despite of its superior accuracy. This paper presents a finite volume based method for re-parametrising the P2D model for any cell chemistry with uncertainty in determining precise electrochemical parameters. The re-parametrisation is achieved by solving a quadratic form of the Butler-Volmer equation and modifying the anode open circuit voltage based on experimental values. Thus the only experimental result, needed to re-parametrise the cell, reduces to the measurement of discharge voltage for any C-rate. The proposed method is validated against the 1C discharge data and an actual drive cycle of a NCR18650BD battery with NCA chemistry when driving in an urban environment with frequent accelerations and regenerative braking events. The error limit of the present model is compared with the electro-chemical prediction of LiyCoO2 battery and found to be superior to the accuracy of the model presented in the literature

Developing a model for analysis of the cooling loads of a hybrid electric vehicle by using co-simulations of verified submodels

The requirement for including the air-conditioning and the battery-cooling loads within the energy efficiency analyses of a hybrid electric vehicle is widely recognized and has promoted system-level simulations and integrated modelling, escalating the challenge of balancing the accuracy and the speed of simulations. In this paper, a hybrid electric vehicle model is created through co-simulation of the passenger cabin, the air conditioning, the battery cooling, and the powertrai. Calibration and verification of the submodels help determine their accuracy in representing the target vehicle and achieve a balance between the model fidelity and the simulation speed. The result is a model which has a higher accuracy and a higher speed than those of similar models developed previously and which provides a reliable tool for a thorough investigation of the cooling loads for different ambient conditions and different duty cycles

A study of the open circuit voltage characterization technique and hysteresis assessment of lithium-ion cells

Among lithium-ion battery applications, the relationship between state of charge (SoC) and open circuit voltage (OCV) is used for battery management system operation. The path dependence of OCV is a distinctive characteristic of lithium-ion batteries which is termed as OCV hysteresis. Accurate estimation of OCV hysteresis is essential for correct SoC identification. OCV hysteresis test procedures used previously do not consider the coupling of variables that show an apparent increase in hysteresis. To study true OCV hysteresis, this paper proposes a new test methodology. Using the proposed methodology, OCV hysteresis has been quantified for different lithium-ion cells. The test results show that a battery's OCV is directly related to the discharge capacity. Measured battery capacity can vary up to 5.0% depending on the test procedure and cell chemistry. The maximum hysteresis was found in a LiFePO4 (LFP) cell (38 mV) and lowest in the LTO cell (16 mV). A dynamic hysteresis model is used to show how better prediction accuracy can be achieved when hysteresis voltage is a function of SoC instead of assuming as a constant. The results highlight the importance of the testing procedure for OCV characterisation and that hysteresis is present in other Li-ion batteries in addition to LFP

The effect of pre-analysis washing on the surface film of graphite electrodes

Electrodes are routinely washed to remove electrolyte deposits, salt, and high boiling point solvents prior to analysis with surface-sensitive techniques. The effect of washing on the surface films of graphite electrodes from LiCoO2/graphite cells, which contained varying amounts of vinylene carbonate (VC), was investigated by comparing the microstructure and chemical composition. We confirmed that there are two different kinds of films on the surface of the electrodes: one at low and one at high VC content concentration. Far from being limited to remove extraneous salt deposits from the surface of the sample, DMC washing was found to completely remove one and to affect the composition of deeper strata in the other