Search

This paper investigates the model development of the state-of-power (SoP) estimation for a 43 Ah large-capacity prismatic nickel-manganese-cobalt oxide (NMC) based lithium-ion cell with a thorough aging investigation of the cells’ internal resistance increase. For a safe operation of the vehicle system, a battery management system (BMS) integrated with SoP estimation functions is crucial. In this study, the developed SoP model used for the estimation of power throughout the lifetime of the cell is coupled with a dual-polarization equivalent-circuit model (DP_ECM) for achieving the precise estimation of desired parameters. The SoP model is developed based on the pulse-trained internal resistance evolution approach, and hence the power is estimated by determining the rate of internal resistance increase. Hybrid pulse power characterization (HPPC) test results are used for extraction of the impedance parameters. In the DP_ECM, Coulomb counting and extended Kalman filter (EKF) state estimation methods are developed for the accurate estimation of the state of charge (SoC) of the cell. The SoP model validation is performed by using both dynamic Worldwide harmonized Light vehicles Test Cycles (WLTC) and static current profiles, achieving promising results with root-mean-square errors (RMSE) of 2% and 1%, respectively.

Lithium-ion capacitors (LiC) are hybrid energy storage systems (ESS) combining the advantages of lithium-ion batteries and electric double-layer capacitors, including longer lifetime, high power, and energy densities. LiCs are popular for high-power applications where fast charge and discharge driving profiles are demanded from electric vehicles (EV). However, LiCs generate excess heat when they are exposed to fast charging/discharging profiles. Therefore, a robust thermal management system (TMS) is crucial, in order to ensure reliable operation. In this study, a novel hybrid TMS based on air-cooling system assisted phase change materials (PCM), heat pipes, and a heat sink is proposed for an LiC module under a 150 A continuous current profile. A very thin aluminum heat sink and flat copper heat pipes were added to the PCM to increase its thermal conductivity. An experimental test bench of the proposed TMS was developed, and the temperature distribution of the module for each of the individual LiC cells was studied. The maximum temperature of the module under natural convection, when there was not any cooling system, reached almost 59.8 °C. The experimental results showed that after using the proposed hybrid TMS, the hottest cell reached 36.18 °C while the coldest cell reached 35.54 °C. Therefore, 39.5% improvement could be seen during the whole charge and discharge process after 3000 s. Moreover, the temperature difference within the module, of four LiCs, was around 0.64 °C, which was exceptional.

Jute is a cheap, eco-friendly, widely available material well-known for its cooling properties. In electric vehicles (EVs), dissipating a huge amount of the heat generated from lithium-ion batteries with an efficient, light, and low-power consumption battery thermal management system (BTMS) is required. In our previous study, jute fibers were proposed and investigated as a novel medium to enhance the cooling efficiency of air-based battery thermal management systems. In this paper, as the first attempt, jute was integrated with a phase change material (PCM) passive cooling system, and the thermal performance of a 50 Ah prismatic battery was studied. Temperature evolution, uniformity, and cooling efficiency were investigated. A comparison between the thermal behavior of the air-based BTMS and PCM-assisted cooling system was performed. The results indicated that adding jute to the BTMS increased the cooling efficiency and especially decreased the temperature development. Furthermore, the temperature difference (ΔT) efficiency was enhanced by 60% when integrating jute with PCM, and temperature uniformity improved by 3% when integrating jute with air-based BTMS. This article compared the integration of jute with active cooling and passive cooling; thus, it shed light on the importance of jute as a novel, eco-friendly, lightweight, cheap, available, and nontoxic material added to two strategies of BTMS. The setup was physically made and experimentally studied for the purpose of BTMS optimization.

Solid-state batteries (SSBs) are gaining attention as they promise to provide better safety and a higher energy density than conventional liquid electrolyte batteries. Solid polymer electrolytes (SPEs) are promising candidates due to their flexibility providing better interfacial contact between electrodes and the electrolyte. However, SPEs exhibit very low ionic conductivity at ambient temperatures, which prevents their practical use in batteries. Herein, a simple and effective technique of hot press rolling is demonstrated to improve ionic conductivity and, hence, the performance of polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP)-based solid polymer electrolyte. Applying hot press rolling to the electrolyte membrane induced structural changes in the grain boundaries, which resulted in a reduction in the crystallinity of the material and, hence, an increase in the amorphous phase of the material, which eased the movement of the lithium ions within the material. This technique also improved the surface of the membrane, making it homogeneous and smoother, which resulted in better interfacial contact between the electrodes and electrolyte. Electrochemical tests were carried out on electrolyte membranes treated with and without hot press rolling to evaluate the effect of the treatment. The hot pressed electrolyte membrane showed significant improvements in its ionic conductivity and transference number. The cycling performance of the LFP/Li batteries using a hot press rolled electrolyte was also evaluated, which gave a specific discharge capacity of 134 mAh/g at 0.1 C. These results demonstrate that hot press rolling can have a significant effect on the electrochemical performance of solid polymer electrolytes.

Lithium-ion capacitor technology (LiC) is well known for its higher power density compared to electric double-layer capacitors (EDLCs) and higher energy density compared to lithium-ion batteries (LiBs). However, the LiC technology is affected by a high heat generation problem in high-power applications when it is continuously being charged/discharged with high current rates. Such a problem is associated with safety and reliability issues that affect the lifetime of the cell. Therefore, for high-power applications, a robust thermal management system (TMS) is essential to control the temperature evolution of LiCs to ensure safe operation. In this regard, developing accurate electrical and thermal models is vital to design a proper TMS. This work presents a detailed 1D/3D electro-thermal model at module level employing MATLAB/SIMULINK® coupled to the COMSOL Multiphysics® software package. The effect of the inlet coolant flow rate, inlet coolant temperature, inlet and outlet positions, and the number of arcs are examined under the cycling profile of a continuous 150 A current rate without a rest period for 1400 s. The results prove that the optimal scenario for the LCTMS would be the inlet coolant flow rate of 500 mL/min, the inlet temperature of 30 °C, three inlets, three outlets, and three arcs in the coolant path. This scenario decreases the module’s maximum temperature (Tmax) and temperature difference by 11.5% and 79.1%, respectively. Moreover, the electro-thermal model shows ±5% and ±4% errors for the electrical and thermal models, respectively.

This work presents a real-life demonstration of 23 heavy-duty (HD) public electric buses (e-buses) in Jaworzno, Poland, with three lengths: 8.9 m, 12 m, and 18 m. The e-bus demo is based on the development of baseline e-buses to optimize the operational cost based on technical optimization. The demo aims to switch public transportation from internal combustion engine vehicles (ICEVs) to electric ones to minimize CO2emissions. The e-buses are equipped with standard charging solutions, which are plug-in charging with Combined Charging System Type 2 (CCS2, Combo 2) and pantograph-up (Type B). The CCS2 solution is used for overnight slow/normal charging (NC) in the depot of the e-bus operator, whereas the pantograph charging solutions are installed along the e-buses routes and used for fast charging (FC) when the e-buses are stopped for a short time. In Jaworzno, there are 20 chargers with CCS2 in the depot of the e-bus operator and 12 pantograph-up (Type B solution) fast-charging stations. This work studies the technical operations and operational costs of the e-bus fleet, and the impact of the NC and FC solutions on the Li-ion battery packs and on the grid. The uncoordinated/standard and coordinated charging (smart charging) based on load shifting were investigated to study the impact of e-bus fleet integration on the distribution grid. The exploited data in this study were collected from the data logger devices, which are installed on the e-buses and record over 46 signals. Data from over one year were collected, and some sample data were processed and analyzed to study the technical and economic operations of the e-bus fleet.

Thermal management is the most vital element of electric vehicles (EV) to control the maximum temperature of module/pack for safety reasons. This paper presents a novel passive thermal management system (TMS) composed of a heat sink (HS) and phase change materials (PCM) for lithium-ion capacitor (LiC) technology under the premise that the cell is cycled with a continuous 150 A fast charge/discharge current rate. The experiments are validated against numerical analysis through a computational fluid dynamics (CFD) model. For this purpose, a comprehensive electro-thermal model based on an equivalent circuit model (ECM) is designed. The designed electro-thermal model combines the ECM model with the thermal model since the performance of the LiC cell highly depends on the temperature. Then, the robustness of the model is evaluated using a precise second-order ECM. The extracted parameters of the electro-thermal model are verified by the experimental results in which the voltage and temperature errors are less than ±5% and ±4%, respectively. Finally, the thermal performance of the HS-assisted PCM TMS is studied under the fast charge/discharge current rate. The 3D CFD results exhibit that the temperature of the LiC when using the PCM-HS as the cooling system was reduced by 38.3% (34.1 °C) compared to the natural convection case study (55.3 °C).

In electrified vehicle applications, understanding the battery characteristics is of great importance as it is the state-of-art principal energy source. The key battery parameters can be identified by one of the robust and nondestructive characterization techniques, such as electrochemical impedance spectroscopy (EIS). However, relaxing the battery cell before performing the EIS method is crucial for the characterization results to be standardized. In this study, the three most common and commercially available lithium-ion technologies (NMC/graphite, LFP/graphite, NCA/LTO) are investigated at 15–45 °C temperature, in the range of 20–80% state of charge (SoC) and in fresh and aged state of health (SoH) conditions. The analysis shows that the duration of the relaxation time before impedance measurement has an impact on the battery’s nonlinear behavior. A rest time of 2 h can be proposed, irrespective of battery health condition, considering neutral technology-based impedance measurement. An impedance growth in ohmic and charge transfer characteristics was found, due to aging, and the effect of rest periods was also analyzed from an electrochemical standpoint. This experimental data was fitted to develop an empirical model, which can predict the nonlinear dynamics of lithium technologies with a 4–8% relative error for longer rest time.

The brushless doubly fed reluctance machine (BDFRM) is receiving an increased amount of attention from the research community thanks to its potential as an alternative drive for variable speed applications, both as motor and generator. Currently, the sizing of the BDFRM in the literature is based on the model of an ideal axially laminated rotor (ALR) and discrepancies are hidden in compensation factors which are in turn tuned with a finite element analysis (FEA). This paper proposes an analytical framework to accurately model the air gap field modulation, and by extension the torque density, of the BDFRM with ducted segmental rotor (DSR) and salient pole rotor (SPR). The results are verified with FEA and validated on a BDFRM prototype.

This paper analyses how the total cost of ownership (TCO) of electric light commercial vehicles change with the number of kilometers driven, the period of ownership, the residual value of the battery, and different fiscal incentives, as well as a kilometer charging scheme. This paper demonstrates that a kilometer-based charge and reduced fiscal incentives for conventional vans can drastically improve the TCO of electric commercial light duty vehicles. Second life applications for batteries could also have a strong impact on the TCO of electric vans as they could retrieve a better residual value. Finally, the paper shows that the TCO of electric vans can be optimized based on its usage. These are important findings given the ambitious objective of carbon free city logistics by 2030. Adoption of electric vans remains very low and this paper offers an up to date analysis to stimulate the electrification of light commercial vehicles, a segment that is growing fast in city logistics.

Electric vehicles (EVs) are recognized as promising options, not only for the decarbonization of urban areas and greening of the transportation sector, but also for increasing power system flexibility through demand-side management. Large-scale uncoordinated charging of EVs can impose negative impacts on the existing power system infrastructure regarding stability and security of power system operation. One solution to the severe grid overload issues derived from high penetration of EVs is to integrate local renewable power generation units as distributed generation units to the power system or to the charging infrastructure. To reduce the uncertainties associated with renewable power generation and load as well as to improve the process of tracking Pareto front in each time sequence, a predictive double-layer optimal power flow based on support vector regression and one-step prediction is presented in this study. The results demonstrate that, through the proposed control approach, the rate of battery degradation is reduced by lowering the number of cycles in which EVs contribute to the services that can be offered to the grid via EVs. Moreover, vehicle to grid services are found to be profitable for electricity providers but not for plug-in electric vehicle owners, with the existing battery technology and its normal degradation.

This paper proposes an optimal design for hybrid grid-connected Photovoltaic (PV) Battery Energy Storage Systems (BESSs). A smart grid consisting of PV generation units, stationary Energy Storage Systems (ESSs), and domestic loads develops a multi-objective optimization algorithm. The optimization aims at minimizing the Total Cost of Ownership (TCO) and the Voltage Deviation (VD) while considering the direct and indirect costs for the prosumer, and the system stability with regard to intermittent PV generation. The optimal solution for the optimization of the PV-battery system sizing with regard to economic viability and the stability of operation is found while using the Genetic Algorithm (GA) with the Pareto front. In addition, a fuzzy logic-based controller is developed to schedule the charging and discharging of batteries while considering the technical and economic aspects, such as battery State of Charge (SoC), voltage profile, and on/off-peak times to shave the consumption peaks. Thus, a hybrid approach that combines a Fuzzy Logic Controller (FLC) and the GA is developed for the optimal sizing of the combined Renewable Energy Sources (RESs) and ESSs, resulting in reductions of approximately 4% and 17% for the TCO and the VD, respectively. Furthermore, a sensitivity cost-effectiveness analysis of the complete system is conducted to highlight and assess the profitability and the high dependency of the optimal system configuration on battery prices.

In this research, twenty-four high capacity (1360 mAh) NMC622/Si-alloy Li-ion full pouch cells with high silicon-alloy content (55%) are cycle aged under seven different cycling conditions to study the effect of different stressors on the cycle life of Si-anode full cells, among which are the effect of ambient temperature, Depth of Discharge (DoD) and the discharge current. The cells are volumetrically constrained at an optimal initial pressure to improve their cycle life, energy and power capabilities. Furthermore, the innovative test setup allows measuring the developed pressure as a result of repeated (de-)lithiation during battery cycling. This uniquely vast testing campaign on Si-anode full cells allows us to study and quantify independently the influence of different stress factors on their cycle life for the first time, as well as to develop a new capacity fade model based on an observed linear relationship between capacity retention and total discharge capacity throughput.

This paper presents the results regarding the thermal characterisation and modelling of high energy lithium-ion battery cells at both room (25 &deg, C) and cycling (35 &deg, C) temperatures. In this work two types of Nickel Manganese Cobalt (NMC) batteries are studied: a fresh (or uncycled) and an aged (or cycled) battery cells. The ageing of the studied NMC battery cells is achieved by means of accelerated ageing tests (i.e., repetition of numerous charge and discharge cycles) at 35 &deg, C cycling temperature. Temperature at the surface of the battery cells is characterised, with a set of three discharge current rates 0.3C (i.e., 6 A), 1C (i.e., 20 A) and 2C (i.e., 40 A), and the evolutions at three different locations on the surface of the battery cells namely, at the top, in the center and at the bottom regions are measured. In addition, temperature and ageing dependent electrochemical-thermal modelling of the uncycled and cycled battery cells is also successfully accomplished in case of both room and cycling temperatures. Numerical simulations were carried out in case of high 2C constant current rate, and the assessment of the modelling accuracy by comparison of the predicted battery cells voltage and temperature with respect to the experimental data is further presented. With this paper, thermal performances of battery cells prior and after long-term cycling are evaluated at the cycling temperature, next to the ambient temperature. Hence, thermal characterisation and modelling results are more closely reflecting that encountered by the battery cells in real cycling conditions, so that their performances are believed in this way to be more objectively evaluated.

In this article, two techniques that are congruous with the principle of control theory are utilized to estimate the state of health (SOH) of real-life plug-in hybrid electric vehicles (PHEVs) accurately, which is of vital importance to battery management systems. The relation between the battery terminal voltage curve properties and the battery state of health is modelled via an adaptive neuron-fuzzy inference system and a group method of data handling. The comparison of the results demonstrates the capability of the proposed techniques for accurate SOH estimation. Moreover, the estimated results are compared with the direct actual measured SOH indicators using standard tests. The results indicate that the adaptive neuron-fuzzy inference system with fifteen rules based on a SOH estimator has better performances over the other technique, with a 1.5% maximum error in comparison to the experimental data.

Smart charging is related to a possible adjustment of the charging sequences with some energetic constraints. It can be defined in different ways, namely depending on the specific objectives. However, they all result in similar consequences for the charging sequences, with regard to conventional charging: potential delay, interruption(s) and power modulation of the charging cycles. It is commonly admitted that smart charging will be necessary to face the growing deployment of EVs, namely for the local grid operators. Moreover, from the user point of view, smart charging can be seen as an additional motivation for the choice of an EV instead of a conventional car, if e.g. lower electricity tariffs are proposed for charging flexibility. In this paper, a quantitative evaluation is performed of EV battery ageing, in function of the charging conditions, with a special focus on the smart charging specificities. The study is based on real data from a three years continuous monitoring of five Peugeot iOn cars, a first of a kind campaign that was performed in Belgium in the Brussels area during the period 2011-2014. Different use profiles and charging patterns were observed. Among other elements, battery capacity and battery efficiency and their evolution in time were calculated, taking into account various factors, such as the seasonal impacts. It will first be highlighted that, whatever their charging patterns, all the considered cars are showing a significant flexibility potential, making them good candidates for smart charging. The impact of smart charging on battery ageing will then be discussed, with a focus on the charging frequency, the average state of charge and the impact of faster versus slower charge on battery capacity. This long time monitoring period allows to clearly identify the time evolution trends, leading to unique conclusions from the real life.

Electric vehicle (EV) energy consumption is variable and dependent on a number of external factors such as road topology, traffic, driving style, ambient temperature, etc. The goal of this paper is to detect and quantify correlations between the kinematic parameters of the vehicle and its energy consumption. Real-world data of EV energy consumption are used to construct the energy consumption calculation models. Based on the vehicle dynamics equation as underlying physical model, multiple linear regression is used to construct three models. Each model uses a different level of aggregation of the input parameters, allowing predictions using different types of available input parameters. One model uses aggregated values of the kinematic parameters of trips. This model allows prediction with basic, easily available input parameters such as travel distance, travel time, and temperature. The second model extends this by including detailed acceleration data. The third model uses the raw data of the kinematic parameters as input parameters to predict the energy consumption. Using detailed values of kinematic parameters for the prediction in theory increases the link between the statistical model and its underlying physical principles, but requires these parameters to be available as input in order to make predictions. The first two models show similar results. The third model shows a worse fit than the first two, but has a similar accuracy. This model has great potential for future improvement.

International audience; This paper presents the electrical and thermal behaviour of an advanced lithium-ion capacitor (LIC) based rechargeable energy storage systems. In the proposed study, an extended statistical analysis has been performed to evaluate the main electrical parameters such as resistance, power, capacitance, rate capabilities, variation between cells and thermal parameters. Based on the performed analysis, an electrical model has been developed for dimensioning and evaluation of various applications based on lithium-ion capacitor technology.

The powertrain control strategy and component sizing can significantly influence the vehicle performance, cost and fuel economy. This paper presents an evaluation study of the current and future Fuel Cell Hybrid Vehicles (FCHEVs) powertrains from the point of view of the fuel economy, volume, mass and cost. In this research, different FCHEV powertrains (such as Fuel Cell/Supercapacitor (FC/SC), Fuel Cell/Battery (FC/B), and FC/SC/B) and different control strategies are designed and simulated by using Matlab/Simulink. In this paper, two standard driving cycles (NEDC and FTP75) are used to evaluate the fuel consumption. Within this study, two control strategies based on the knowledge of the fuel cell efficiency map are implemented to minimize the hydrogen consumption of the FCHEV powertrains. These control strategies are control strategy based on Efficiency Map (CSEM) and control strategy based on Particle Swarm Optimization (CSPSO). Furthermore, a comparative study of different FCHEV powertrains is provided for adequately selecting of the proper FCHEV powertrain, which could be used in industrial applications.

In 2011 the Flemish government launched the Living Labs Electric Vehicles, consisting of 5 different platforms each differing in technology, scope, size and use patterns. For the build-up of these platforms, the Flemish government relies on private companies, local authorities and research institutes. These platforms serve as an environment in which platform members as well as other partners can carry out experimental research related to the roll-out of electric vehicles (EVs) and EV fleets. A total financial investment of ±30 million € was made, equally divided between the private sector and the government, and an introduction of 600 electric vehicles and 600 new electric charging points is aimed for. The addressed research topics within these living labs include the assessment of the driving range of the EVs, the assessment of the implemented drivetrain technologies and charging infrastructure, travel- and purchase behaviour, market potential analyses, the development of new business cases, the development of new services and products, total cost of ownership analyses, environmental impact analyses, and social acceptance. In addition, with respect to the charging infrastructure, standardization issues, interoperability of the charging systems, and billing and roaming procedures are studied. A wide variety of stakeholders related to electric mobility is involved in these living labs, ranging from knowledge centres, automotive manufacturers, electricity producers and distributors, service providers. public transport companies and local authorities, to fleet owners and end users. This paper gives an overview of the 5 launched platforms: EVA, iMOVE, Olympus, EV TecLab and Volt-Air.

This paper presents a supercapacitor (SC) module connected in parallel with fuel cell (FC) stack to supply a high-performance Z-Source Inverter (HP-ZSI) feeding a three phase induction motor for hybrid electric vehicles applications. The supercapacitor is connected between the input diode and the bidirectional switch of the highperformance ZSI topology. The indirect field-oriented control (IFOC) method is used to control an induction motor speed during motoring and regenerative braking operations to produce the modulation index and a dual loop controller is used to control the Z-network capacitor voltage to produce the shoot-through duty ratio. MATLAB simulation results verified the validity of the proposed control strategy during motoring and regenerative braking operations.

This paper investigates whether the vehicle taxation system in Belgium is stimulating the demand of clean vehicle technologies. A life cycle cost analysis will be performed to evaluate the cost-efficiency of several vehicle technologies within the current fiscal system. This life cycle cost will be weighted against the environmental performance of each vehicle to discover the market potential of environmental friendly vehicles and to define necessary fiscal regulations. Additionally, the yearly taxes and external costs (environmental, congestion, accident costs) of each vehicle will be compared, identifying the strenghts and distortions of the Belgian fiscal system with respect to the promotion of clean vehicles. Moreover, it will be examined whether a new vehicle taxation system, based on the environmental performance of vehicles, would be effective in tackling the current distortions while keeping the good incentives for stimulating the demand of clean vehicle technologies. This new vehicle taxation system will be based on a environmental rating tool, the so-called Ecoscore. The Ecoscore enables a comparison of the environmental burden caused by vehicles with different drive trains and using different fuels and is in this respect a very appropriate instrument to introduce a technology neutral reform of the fiscal system. By calculating the tax burden of several vehicles within the current and new fiscal system, it will be assessed whether this new fiscal system is able to evoke a shift in the composition of the vehicle fleet towards a more environmental friendly one.

A typical traction system consists of two main components, an energy reservoir (e.g. a battery or generator) and an energy converter (e.g. an electric motor). In many cases traction systems are subjected to dynamic loads, as the energy converter should be able to deliver the demanded energy at any time. If only one energy reservoir is available, optimal use becomes difficult. In order to respond to energy peak demands these energy reservoirs are often overdimensioned, with a suboptimal energy yield in regime conditions as a result. Energy reservoirs are defined by two key parameters, being the energy density and the power density. Ideally an energy reservoir should offer both a high energy and a high power density. A typical energy reservoir has a high energy density, but a limited power density, whereas new components, such as supercapacitors, offer low energy, but high power density. Supercapacitors are electrochemical energy storage components and offer new solutions for various applications. The question at hand is if the combination of a supercapacitor and relatively low power energy reservoir can result in a more ideal energy storage system. In systems using a battery as energy storage unit, the use of a supercapacitor peak power unit could result in significant improvements. As traction batteries were designed for low power density applications, high peak loads result in higher voltage- en yield-drops. Because a supercapacitor unit can be used to relief the battery system from these peak loads, the battery unit can be dimensioned for optimized regime load conditions, resulting in a better yield point and thus in a better global system yield and less energy use. Furthermore, the supercapacitor unit has an additional plus, because not only it can answer to high power peak demands, it is also able to be charged very fast. This energy can come from the available energy reservoir, the battery, or from the traction system working as a generator. This energy saving regenerative feature can be implemented inmany ways, such as recovery of braking energy in vehicles, elevators, etc. The optimal combination of both a battery unit and a supercapacitor unit is not realized by just connecting them in parallel. The supercapacitor's charge is proportional to the potential difference or voltage and the energy stored in the supercapacitor is proportional to the square voltage. In order to fully utilize the charge and thus the energy contained in the supercapacitor, it is desirable to let the voltage change in a broad window. To realize this, a two-way DC-DC converter between the supercapacitor unit and the semi-constant battery DC-bus is necessary. The proposed review paper will give an overview of state-of-the-art technology regarding supercapacitors (leakage currents and balancing), batteries (lifecycle assessment in regime and heavy load conditions) and their combination using a converter (topology assessment) and power management strategy. To conclude the paper will comprise an estimate of such a system's potential for several applications.