World Electr. Veh. J., Volume 7, Issue 1 (March 2015) – 18 articles , Pages 1-172

In order to extend the product applications into plug-in hybrid electric vehicle field, a high capacity lithium-ion battery is configured and matched to the previous compound power-split hybrid transmission which is based on a modified ravigneaux gear set with two additional brake clutches. The equivalent lever diagrams are used to investigate the operating modes for the hybrid system, and its dynamic and kinematic characteristics in equations are derived. To evaluate the economy and power performance of the plug-in hybrid vehicle, a forward-looking simulation platform and components model are established. In addition, the simulating results of key power and economy tests are demonstrated. Results show that the proposed powertrain configuration can be well used for plug-in applications, and the economy and power performance can be further improved. Full article

Two test programs were conducted to investigate the on-road performance of model year 2012 Chevrolet Volts in Ottawa, Ontario, Canada. Specific testing routes were defined for various types of city and highway driving. Data loggers and additional instrumentation were installed in the vehicles to accurately monitor variables indicating the use of electricity for driving, as well as the use of fuel by the gasoline engine. The vehicles were tested during various seasons of the year to record their performance over the full range of climate conditions representative for a large part of Canada (from -27 °C to +37 °C). The test results were subsequently processed and analysed to compare the Volt’s performance in charge depletion mode (electric drive) to its operation in charge sustaining mode (hybrid drive). A ‘Gasoline Displacement Factor’ was introduced, which reflects the amount of grid electricity needed to replace one litre of gasoline used for driving the Volt. Test results show very low Gasoline Displacement Factors of 2 – 3.5 kWh/L for summer driving, while values of 3 – 9 kWh/L were observed for winter driving. The test results were also used to evaluate the additional amount of energy that the vehicles would need for driving, and cabin conditioning (heating in winter, air conditioning in summer) under conditions different from the more optimal 20-25 °C temperature range used for most standard performance tests. The Volt’s relative performance under extreme temperature conditions was compared to those of conventional gasoline vehicles, hybrid electric vehicles and battery electric vehicles. Additionally, recommendations for a more optimal use of the Volt under extreme temperature conditions are provided. Full article

Environment Canada (EC) and Natural Resources Canada (NRCan) separately tested two 2012 Chevrolet Volts between 2013 and 2014 in Ottawa, Ontario on public roads in the summer and winter months using realistic cabin-climate control settings. More than 1300 trips were conducted over nine routes: three city, one congested, two arterial, one highway and two expressway routes. EC tests recorded cabin conditioning, traction battery and 12V accessory power, select vehicle component temperatures, regulated emission rates and exhaust flow, and DC charge energy. Both NRCan and EC tests measured cumulative electric distance, select CANbus signals and AC grid supply charge energy. Results from these studies were analysed to evaluate the overall performance of the Chevrolet Volt on public roads in climates representative of most of Canada (-27°C to 37°C) using realistic accessory settings. At warm temperatures (~25°C) the Chevrolet Volt’s on-road all-electric range generally exceeded the U.S. EPA sticker rating (57.9km), while at cold (<0°C) and hot temperatures (>25°C) the all-electric range decreased to as low as 27.5km and 47.3km, respectively. Cabin conditioning energy was found to be directly related to the difference between ambient and cabin temperature, except at low temperatures (<0°C) when the 1.4L engine activates to assist the thermal management system. On average, heating the cabin in the winter months consumed significantly more electric energy than cooling the cabin in the summer months. Summer city and highway driving resulted in the lowest energy consumption (Wh/km), while congested and expressway driving cycles resulted in the highest. In the winter months, many differences between the drive cycles were not discernible due to the high cabin conditioning energy consumptions. Full article

Hybrid electric vehicle (HEV) uses internal combustion engine (ICE) and electrical power, so it has the advantages of both ICE vehicle and electrical vehicle (EV) and overcomes their disadvantages. And seriesparallel hybrid is the combination of series and parallel structures, thus it possesses the major features of both and more plentiful operation modes than one of them alone. In this paper, a series-parallel HEV model is built by using Matlab/Simlunk, which constitutes of vehicle longitudinal dynamics model, tire model, an ICE model, battery model, a DC/DC converter model, a motor drive model, a generator drive model, a speed coupling device model (planetary gear mechanism), and a torque coupler device model. Control scheme of HEV is presented. And Simulation results testify the effectiveness of the HEV model. Full article

Drive cycle pattern is different for different countries which depends on their traffic density, road condition and driver discipline. Drive cycle influences HEV`s components design, sizing and their ratings. Standard drive cycle data doesn't reveal much information to determine efficient and economic design of HEV`s components. In this research paper measurement and analysis of real time Indian road drive cycles (IRDC) are carried out for urban roads, state highway, national highway and express Highway where vehicles have their most run. Real time drive cycle data will expose impact of driver’s skills, traffic, road conditions and short acceleration / deceleration period, which can be represented on drive cycle chart. Analysis of IRDC in terms of rate of acceleration and deceleration, top speed, average speed with road length and analysed mathematically to find energy and power required for acceleration, normal operation and energy harvested during deceleration. Based on information from IRDC HEV`s components initial size are estimated. Initial estimated size is optimized to make HEV`s components design more efficient and economic. Teaching and learning based optimization algorithm (TLBO) and Multi objective genetic algorithm (MOGA) are used to optimize HEV`s components. Constraint of optimization algorithm are like engine and motor rating should be selected such that it has effective top speed with enough acceleration capability and can run enough distance to reach destination according to Indian urban, state, national and express highway pattern where cities are very closed compared with other countries and its regeneration component design should able to harvest maximum deceleration energy. For economic operation of HEV’s, running cost in terms of Rs. / Km. should be minimum. Full article

Argonne National Laboratory has analyzed the control behavior of advanced vehicles, such as hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs), to develop simulation models and to reproduce the performance of vehicles with simulation techniques. Since many of the novel and advanced studies about transportation technologies done at Argonne use these simulation techniques, they must be well-validated to conduct and support these studies. To improve its research ability, Argonne built a new testing facility that can test vehicles under different thermal conditions (e.g., –7°C or 35°C), and it has analyzed the controls and performance of several advanced vehicles under these conditions. Further, Argonne has used the analyzed results to develop thermal component models that reproduce the thermal behavior of the vehicles. A main reason to develop thermal models is that the thermal conditions have such a significantly large impact on vehicle performance, especially with regard to advanced vehicles like HEVs or PHEVs. For instance, engine and battery efficiencies must decrease at low temperatures since the battery might not be able to provide enough power if it is very cold. Moreover, the climate control system still has a great demand for additional energy under very cold weather conditions even if the engine is not operating at all. The test data obtained from Argonne’s Advanced Powertrain Research Facility (APRF) are analyzed in order to understand the thermal impacts on controls and performance, and the thermal models are developed based on the analyzed results and validated with the test data. In comparative studies, the simulation models have been found to reproduce fuel consumption that is very close to the fuel consumption obtained from the tests. Full article

The new freedoms in design that electric powertrains offer lead to a wide variety of configurations to consider when developing an electric vehicle (EV) from scratch. Furthermore, the strong relation of the battery size with vehicle weight, range and performances leads to a set of interrelated dependencies that can result in many design loops to fulfil the targets and regulations simultaneously. The paper presents a tool that integrates the main relations regarding vehicle targets, market and regulations constraints and plots them as restrictions for vehicle development. As a result, the tool depicts a set of feasible vehicle configurations that could fulfil the targets. Furthermore, to better assist selection, it also provides a sensitivity analysis of the performances and the user can introduce a cost function depending on vehicle weight and battery size. The tool is aimed at providing an overview of specifications for component selection avoiding detailed vehicle modelling in the early pre-design phase in which vehicle characteristics and even powertrain architecture are unknown. Finally, the tool is evaluated by modelling one of its solutions for passenger car for three different architectures in the simulation software vemSim. Furthermore, for one of the architectures, two control strategies were simulated, leading to a total of four simulations. The results of the simulations are compared to the solution of the pre-design tool to evaluate the level of fidelity and the deviations in the final result that can appear depending on the architecture, components and control strategy. Full article

The specifications that define an automotive development project are established at an early point in the process and define the direction of such a development, and changing these decisions becomes more costly the further the project progresses. Tools to enable better consideration of choice can help prevent this. The tool presented is designed to aid with the decisions needed when embarking on the development of a vehicle that incorporates electric-vehicle technologies and the important choices made regarding the battery pack required by such a vehicle. The tool incorporates a sizing model for determining the number of cells and the configuration required to meet a specified battery requirement. The tool then uses a 1-d model to determine some of the basic thermal and power characteristics that can then be used to inform other parts of the design specification. When attached to a database containing cell information, the tool can pre-select candidate cells to meet the requirement, and rapid execution time of the tool means that it can be used to quickly compare between cell choices, at a level understandable by all stakeholders in the decision making process. Full article

In December, 2014, Toyota Motor Corporation started public sale of FCV "MIRAI" ahead of the world. Toyota Fuel Cell System (TFCS) was aimed to realize the world’s first truly practical FCV, which would be capable of demonstrating the potential of FCVs. TFCS was adopted in MIRAI, enhanced the excellence of FCV, which had the reputation remarkably so far and Toyota drastically reduced the cost of the FC system, which is one of the largest obstacles to the commercialization of FCVs. This paper describes the development of the TFCS and its components, focusing on the approaches taken to accomplish this reduction in cost. Full article

Lithium ion batteries undergo complex electrochemical and mechanical degradation. This complexity is pronounced in applications such as electric vehicles where highly demanding cycles of operation and varying environmental conditions lead to non-trivial interactions of ageing stress factors. This work presents the framework for an ageing diagnostic tool based on identifying the physical parameters of a fundamental electrochemistry-based battery model from non-invasive voltage/current cycling tests. Exploiting the embedded symbolic manipulation tool and global optimiser in MapleSim, computational cost is reduced, significantly facilitating rapid optimisation. The diagnostic tool is used to study the degradation of a 3Ah LiC₆/LiNiCoAlO₂ battery stored at 45℃ at 50% State of Charge for 202 days; the results agree with expected battery degradation. Full article

In electric vehicle (EV) and hybrid electric vehicle (HEV) application, accurate information of state-ofcharge (SOC) and capacity of each cell are required for elaborate SOC/capacity estimation algorithm of the battery pack. However, the measurement of the states of all cells using sophisticated algorithms increases the computation time beyond practicality, because the computation time required for the SOC/capacity estimation of the battery pack is directly affected by the number of unit cells. In this work, a simple SOC and capacity estimation algorithm for Li-ion battery pack is newly proposed by using filtered terminal voltage. The SOC estimation algorithm using filtered terminal voltage extracts an estimated current information from the terminal voltage of the battery pack through equivalent-circuit model (ECM)-based filters without sensing the current. Consequently, it drastically reduces computational steps for the SOC estimation algorithm. With the fact that all the current flowing through the series-connected cells in pack are identical, the estimated current value of each cell should be identical. As a result, it can be known that this algorithm enables us to obtain the relative proportion of SOC/capacity information of each cells and battery pack with minimal complexity increase. To validate the performance of the proposed approach, a scaled-down HEV profile is used for a pack consists of twelve 18650 series-connected Li-ion batteries (12S1P). The experimental results verify the performance of the proposed battery pack SOC estimation algorithm. Full article

A large European Project, named HCV (Hybrid Commercial Vehicles) started in January 2010 with the participation of 18 European organizations (vehicle manufacturers, components integrators and suppliers, and research organizations) and with the scope to develop and demonstrate the next generation of hybrid heavy duty (HD) commercial vehicles by using various types of storage systems. In this project, seven research (AIT, ENEA, University of Pisa) and industrial organizations (IVECO, Volvo, Magna, DimacRed) from various European countries have been working together to experimentally analyse, with electrical and safety tests, the behaviour of Li-ion and supercapacitor cells and modules to support the design and the optimization of the final storage systems to be installed on different HEV (Hybrid Electric Vehicles): urban buses and commercial vans.
This paper summarizes the experimental work carried out at ENEA and is focussed on electrical and safety tests, which fully characterized the selected storage samples according to conventional and testing procedures, tailored on the technical specifications of the HEV under development. Initially, basic characterization testing, together with safety tests, confirmed the technical performances of the two storage technologies, and, subsequently, project-specific testing, including cycle life and accelerating procedures, verified the behaviour in operating conditions, adapted to the selected HEV. The final results substantiated the suitability of the storage systems in powering the commercial hybrid vehicles under development in HCV project, and gave innovative inputs to the definition and validation of mathematical models and control algorithms, not analysed in this paper, to be used in the BMS (battery management systems) for both storage technologies, suitable for thermal management and overall storage control. Full article

Battery performance and lifetime constitute a bottleneck for electric vehicles and stationary electric energy storage systems to penetrate the market. Electrochemical or physics based battery models are one of the engineering tools to enhance their performance. These models should enable us to optimize the cell design and the battery management system. In this study we evaluate the ability of the much used Porous Electrode Model (PEM) to predict the effect of changing cathode density in the overall performance of a Li-Ion cell. We conclude that the PEM is well capable of predicting battery discharge capacities for cells with changing cathode density. Full article

In an electric vehicle, energy recovery during regenerative braking causes recharge periods of high current rate, which might damage the Li-ion traction battery. To determine the impact of regenerative braking on battery aging, an experimental cycle life study has been performed: Driving load profiles with different mag-nitudes of regenerative braking have been applied to high-energy Li-ion cells at different temperatures and states of charge (SoC). An additional calendar life study has enabled an identification of usage-dependent and usage-independent battery aging.After five months of cycling, corresponding to a driven distance of 50,000 km, cell degradation has varied substantially with different operation conditions. Our paper provides valuable new insights on the impact of regenerative braking on battery aging: A higher level of regenerative braking has generally led to reduced battery aging. This can be attributed to a reduction of lithium plating, as the depth of discharge is reduced with an increased amount of charge recovered by regenerative braking. Our study has shown that it is not the short-time recharging with high current rates, but the long-lasting charging periods, even with only low cur-rent rates, that promotes lithium plating. Moreover, the comparison of usage-dependent and usage-independ-ent battery aging has revealed that cyclic aging decreases with temperature, whereas calendar aging increases with temperature. Thus, battery life can be extended by optimized operating conditions.this paper, we provide advice for optimizing the operating conditions for Li-ion battery systems in electric vehicles. Not only regenerative braking, but also temperature and SoC, is considered for optimal operating strategies maximizing battery life. Based on the results of our experimental study, achieving a driven distance of 100,000km with only 10% capacity fade appears to be possible. Such a low battery aging is essential to promote the spread of electric vehicles, as it reduces the total cost of ownership, which is a prerequisite for the long-term success of electric vehicles. Full article

The cost situation for lithium-ion batteries is one of the key limitations for the market potential of electric vehicles and has been covered by several authors from the industry and science sector. This work addresses the relation between active material properties, cell design and vehicle requirements. The results of this investigation show that the efficient use of the cell properties in the vehicle application will be decisive for the competitiveness of OEMs and battery suppliers. The center of the research is a cell model in which different active material properties, cell formats and electrode layouts can be implemented flexibly. Within a constant volume of a standardized cell housing the variation of the electrode loadings leads to relationships between the storable energy and the power of the cell. The costs determined for each specific cell design then allow describing the relation between the power to energy ratio of a cell and its energy specific costs for current and future materials. The optimal cost situation is reached when the P/E-ratio of the cell matches the required P/E-ratio of the storage system. In a broad vehicle portfolio this means a specific cell would be required for each car project. This potentially large number of cell types seems unfavorable for OEMs to handle. Therefore a genetic algorithm optimization is applied to determine the cost-optimal number and specifications of cells to address a certain vehicle portfolio. For these optimizations further restrictions such as voltage level limitations are considered as well. The tool derived from these considerations can support OEMs as well as cell & material suppliers to find the optimal modular kit for their lithium-ion cell strategy considering individual customer requirements. Full article

Degradation mechanisms of lithium iron phosphate battery have been analyzed with calendar tests and cycle tests. To quantify capacity loss with the life prediction equation, it is seen from the aspect of separating the total capacity loss into calendar capacity and real cycle capacity loss. The real cycle capacity loss of total capacity loss was derived by subtracting the calendar capacity loss parts during cycle tests. It is considered that calendar capacity loss is dominated by SEI formation. On the other hand, real cycle capacity loss includes structure disorder of electrodes and promotion of SEI growth such as delamination and regrowth. Generally, the test results indicated that capacity loss increases under high temperature and SOC condition, and SOC range (ΔSOC) is not related to the loss. However, we founded that the test results under 5℃ condition do not exactly show the same tendency of degradation. As a result, the life prediction equation is based on the chemical kinetics and it can only be adopted only beyond the 15℃ temperature limitation. At this time in life prediction equation, to take ΔSOC into consideration and describe the real cycle capacity loss specifically with amounts of lithium-ion intercalation/deintercalation, the processing amount of current is adopted as the standard of capacity degradation instead of the cycle number. Finally, it is considered to be possible that certain reactions such as further structure disorder or lithium plating caused under low temperature. However, we also founded that DC internal resistance tests results indicated that only calendar capacity loss can apply to chemical kinetics. It is necessary to consider the other construction method of the life prediction equation in the future Full article

The aim of this work is the design of an algorithm for on-board determination of the actual capacity of a LiFePO₄ cathode-based lithium-ion battery in electric vehicle applications. The presented approach is based on the detection of the predominant aging mechanisms (in terms of loss of lithium and loss of active material in both electrodes) through the determination of the single electrode voltage curves. The information related to the characteristic length and position of the voltage plateaus which can be gathered during the battery operation can be used to obtain the actual aging state of the cells. The length of the plateaus depends on the respective position that the voltage curves of the single electrodes have in relation to each other. Relating the change of the plateau characteristics with the possible aging mechanism allows the determination of the actual battery aging state in terms of total cell capacity. The work presents a possible implementation of an algorithm for capacity determination based on the described methodology. The algorithm is validated with various differently aged LiFePO₄ cells. Furthermore, the work discusses the ability of the method to detect the actual battery capacity when only part of the quasi-OCV curve is measured. Achieved accuracy and existing limitations are described and discussed in detail. Full article

A lumped Electro-thermal model of a large format high power Li-Ion cell is introduced in this paper. The model is able to meet the real time implementation requirements; hence it finds its application in Battery Management System (BMS) of an Electric Vehicle (EV). The model is evaluated in Hardware in the Loop (HIL) setup to verify online estimation of cell surface and internal temperature estimation for an on-board EV application. In this study, the cell is considered as a single homogeneous layer and the heat is generated in the centre point of the cell and flows in one direction towards the surface. For this modelling purpose, reversible and irreversible heat in the cell is considered. Irreversible heat consists of the Joule heating effect due to internal resistance of the cell, for instance these values are then calculated with sufficient electrical cell model and evaluated both offline and in real time calculation. Reversible heat is a result of entropy effect which can be negative or a positive value depending on the direction of current flow during charging and discharging process of the cell. Other heat transfer mechanism such as conductive heat transfer and convective heat transfer are also included into the model. This paper introduces a reference case test used to calculate the required necessary coefficients both for parameterization of electrical model and thermal model. The battery setup in the laboratory for measuring the cell surface temperature as reference data as well as cell sandwich setup for evaluating the internal temperature of the cells is explained in detail. Fundamental equations to develop the thermal model are introduced and the model is evaluated in both offline and real time mode. Full article