Erik Schaltz

Influence of Battery/Ultracapacitor Energy-Storage Sizing on Battery Lifetime in a Fuel Cell Hybrid Electric Vehicle

Combining high-energy-density batteries and high-power-density ultracapacitors in fuel cell hybrid electric vehicles (FCHEVs) results in a high-performance, highly efficient, low-size, and light system. Often, the battery is rated with respect to its energy requirement to reduce its volume and mass. This does not prevent deep discharges of the battery, which are critical to the lifetime of the battery. In this paper, the ratings of the battery and ultracapacitors are investigated. Comparisons of the system volume, the system mass, and the lifetime of the battery due to the rating of the energy storage devices are presented. It is concluded that not only should the energy storage devices of a FCHEV be sized by their power and energy requirements, but the battery lifetime should also be considered. Two energy-management strategies, which sufficiently divide the load power between the fuel cell stack, the battery, and the ultracapacitors, are proposed. A charging strategy, which charges the energy-storage devices due to the conditions of the FCHEV, is also proposed. The analysis provides recommendations on the design of the battery and the ultracapacitor energy-storage systems for FCHEVs.

Switching Frequency Reduction Using Model Predictive Direct Current Control for High-Power Voltage Source Inverters

In this paper, a novel current control approach called model predictive direct current control (MPDCC) is presented. The controller takes into account the discrete states of the voltage source inverter (VSI), and the current errors are predicted for each sampling period. Voltage vectors are selected by a graph algorithm, whereby the most appropriate vector is chosen based on an optimization criterion. However, this depends on whether the state of the system is transient or steady. In the first case, the current error should be minimized as fast as possible in order to obtain fast dynamics. In the latter one, the VSI switching behavior is optimized since the switching losses account for a large amount of the total converter losses in high-power drive systems. MPDCC has been developed for a general neutral-point isolated resistive-inductive load with an internal voltage source. For demonstration, the presented control strategy has been implemented on a small-scale permanent-magnet synchronous machine drive system with a two-level VSI. This new approach has several advantages. The most important one is that the switching frequency is reduced up to 70% compared to linear control combined with pulsewidth modulation. Second, MPDCC obtains fast dynamic responses, which are already known from, e.g., direct torque control.

Sensorless Model Predictive Direct Current Control Using Novel Second-Order PLL Observer for PMSM Drive Systems

The model predictive direct current control (MPDCC) is a promising control approach for high- power converters. It takes the discrete states of the voltage source inverter (VSI) into account, and the future converter behavior is predicted for each sampling period. Possible voltage vectors are selected by a graph algorithm, and the most appropriate one is chosen based on an optimization criterion in order to obtain high dynamics. Applying this method to sensorless MPDCC drive systems, special observer characteristics are required. For this reason, an angle and speed observer has been designed. The position of the internal voltage vector, i.e., the back electromotive force, is obtained with a phase-locked loop structure. Control strategy and observer have been developed for permanent-magnet synchronous machine drive systems, and they have been implemented on a small-scale system with two-level VSI for demonstration. This new observer has the advantages to combine high bandwidth with disturbance robustness and can be applied to round rotor and salient pole machines. Moreover, the possibility to combine MPDCC with a sensorless observer is shown.

Design and Control of a Multiple Input DC/DC Converter for Battery/Ultra-capacitor Based Electric Vehicle Power System

Battery/Ultra-capacitor based electrical vehicles (EV) combine two energy sources with different voltage levels and current characteristics. This paper focuses on design and control of a multiple input DC/DC converter, to regulate output voltage from different inputs. The proposed multi-input converter is capable of bi-directional operation and is responsible for power diversification and optimization. A fixed switching frequency strategy is considered to control its operating modes. A portion of New York City Cycle that includes these operation modes is used to perform the analyses.

Investigation of battery/ultracapacitor energy storage rating for a Fuel Cell Hybrid Electric Vehicle

Combining high energy density batteries and high power density ultracapacitors in fuel cell hybrid electric vehicles (FCHEV) results in a high efficient, high performance, low size, and light system. Often the batteries are rated with respect to their energy requirement in order to reduce their volume and mass. This does not prevent deep discharges of the batteries, which is critical to their lifetime. In this paper, the ratings of the batteries and ultracapacitors in a FCHEV are investigated. Comparison of system volume, mass, efficiency, and battery lifetime due to the rating of the energy storage devices are presented. It is concluded, that by sufficient rating of the battery or ultracapacitors, an appropriate balance between system volume, mass, efficiency, and battery lifetime is achievable.

Evaluation of Fuel-Cell Range Extender Impact on Hybrid Electrical Vehicle Performance

The use of electric vehicles (EVs) is advantageous because of zero emission, but their market penetration is limited by one disadvantage, i.e., energy storage. Battery EVs (BEVs) have a limited range, and their batteries take a long time to charge, compared with the time it takes to refuel the tank of a vehicle with an internal combustion engine (ICE). Fuel cells (FCs) can be added to an EV as an additional energy source. These are faster to refill and will therefore facilitate the transition from vehicles running on fossil fuel to electricity. Different EV setups with FC strategies are presented and compared. The results of the setups are presented by range, efficiency, and price. These show the negative effect on the range when purpose-designed setups are driven above the design requirement as the range drops considerably. The simulations also showed the necessity of good FC control when driving in start/stop city cycles. Simulations with the New European Driving Cycle (NEDC) showed that efficiency fell by at least 15% for the FC hybrid EV (FCHEV) when compared with BEVs.

Non-inverting buck-boost converter for fuel cell applications

Fuel cell DC/DC converters often have to be able to both step-up and step-down the input voltage, and provide a high efficiency in the whole range of output power. Conventional negative output buck-boost and non-inverting buck-boost converters provide both step-up and step-down characteristics. In this paper the non-inverting buck-boost with either diodes or synchronous rectifiers is investigated for fuel cell applications. Most of previous research does not consider the parasitic in the evaluation of the converters. In this study, detailed analytical expressions of the efficiencies for the system composed of fuel cell system and interfacing converter, considering the parasitics, are presented. It is concluded that the implementation with synchronous rectifiers provides the highest efficiency in the whole range of the fuel cell power, and its efficiency characteristic is more suitable for fuel cell applications than the implementation with diodes.

Electrical Vehicle Design and Modeling

Electric vehicles are by many seen as the cars of the future as they are high efficient, produces no local pollution, are silent, and can be used for power regulation by the grid operator. However, electric vehicles still have critical issues which need to be solved. The three main challenges are limited driving range, long charging time, and high cost. The three main challenges are all related to the battery package of the car. The battery package should both contain enough energy in order to have a certain driving range and it should also have a sufficient power capability for the accelerations and decelerations. In order to be able to estimate the energy consumption of an electric vehicles it is very important to have a proper model of the vehicle (Gao et al., 2007; Mapelli et al., 2010; Schaltz, 2010). The model of an electric vehicle is very complex as it contains many different components, e.g., transmission, electric machine, power electronics, and battery. Each component needs to be modeled properly in order prevent wrong conclusions. The design or rating of each component is a difficult task as the parameters of one component affect the power level of another one. There is therefore a risk that one component is rated inappropriate which might make the vehicle unnecessary expensive or inefficient. In this chapter a method for designing the power system of an electric vehicle is presented. The method insures that the requirements due to driving distance and acceleration is fulfilled. The focus in this chapter will be on the modeling and design of the power system of a battery electric vehicle. Less attention will therefore be put on the selection of each component (electric machines, power electronics, batteries, etc.) of the power system as this is a very big task in it self. This chapter will therefore concentrate on the methodology of the modeling and design process. However, the method presented here is also suitable for other architectures and choice of components. The chapter is organized as follows: After the introduction Section 2 describes the modeling of the electric vehicle, Section 3 presents the proposed design method, Section 4 provides a case study in order to demonstrate the proposed method, and Section 5 gives the conclusion remarks.

Datasheet-based modeling of Li-Ion batteries

Researchers and developers use battery models in order to predict the performance of batteries depending on external and internal conditions, such as temperature, C-rate, Depth-of-Discharge (DoD) or State-of-Health (SoH). Most battery models proposed in the literature require specific laboratory test for parameterization, therefore a great majority do not represent an appropriate and feasible solution. In this paper three easy-to-follow equivalent circuit modeling methods based only on information contained in a commercial Li-Ion cell manufacturers datasheet are presented and validated at steady state, comparing simulation results and manufacturers curves. Laboratory results are included in order to demonstrate the accuracy of parameters estimation. Results of each method are presented, compared and discussed for a Kokam SLPB 120216216 53Ah Li-Ion cell.

Individual Module Maximum Power Point Tracking for Thermoelectric Generator Systems

In a thermoelectric generator (TEG) system the DC/DC converter is under the control of a maximum power point tracker which ensures that the TEG system outputs the maximum possible power to the load. However, if the conditions, e.g., temperature, health, etc., of the TEG modules are different, each TEG module will not produce its maximum power. If each TEG module is controlled individually, each TEG module can be operated at its maximum power point and the TEG system output power will therefore be higher. In this work a power converter based on noninverting buck–boost converters capable of handling four TEG modules is presented. It is shown that, when each module in the TEG system is operated under individual maximum power point tracking, the system output power for this specific application can be increased by up to 8.4% relative to the situation when the modules are connected in series and 16.7% relative to the situation when the modules are connected in parallel.