46.2.1 Battery Storage

46.2.2 Ultracapacitor (UC)

Electrochemical double-layer capacitors (EDLCs) or ultracapacitors (UCs) work in much the same way as regular capacitors, in that there is no ionic or electronic transfer, resulting in a chemical reaction (there is no Faradic process). In other words, energy is stored in the electrochemical capacitor by simple charge separation. Therefore, the energy stored in the electrochemical capacitor can be calculated using the same well-known equation that is used for conventional capacitors:

As for the conventional capacitor, the capacitance, C, is proportional to the area, A, of the plates, the permittivity of the dielectric, ϵ, and inversely proportional to the distance, d, between the plates. In general, UCs are designed to have a very high electrode surface area and use high-permittivity dielectric while keeping the current collectors very close. Therefore, UCs attain very high capacitance ratings (kilo-Farads versus milli- and micro-Farads for conventional capacitors). This is achieved by using porous carbon as the current collector rather than metallic strips. The porous carbon collector exhibits a very large surface area, allowing a relatively large amount of energy to be stored at the collector surface. The two electrodes are separated by a very thin porous separator and immersed in an electrolyte, such as propylene carbonate. Due to the high permeability and close proximity of the electrodes, UCs have a low voltage withstand capability (typically 2.5 V).

Currently, there exist five UC technologies in development: carbon/metal fiber composites, foamed (aerogel) carbon, carbon particulate with a binder, doped conducting polymer films on carbon cloth, and mixed metal oxide coatings on metal foil. Current trends indicate that higher energy densities are achievable with a carbon composite electrode, using an organic electrolyte, rather than carbon/metal fiber composite electrode devices, with an aqueous electrolyte.

As described earlier, a UC stores energy by physically separating unlike charges. This has profound implications on cycle life, efficiency, energy, and power density. It must be noted that, typically, a UC depicts long cycle life due to the fact that (ideally) there exist no chemical changes on the electrodes, under normal operation. Furthermore, overall efficiency is superior; it is only a function of the ohmic resistance of the conducting path. In addition, power density is exceptional because the charges are physically stored on the electrodes. Conversely, energy density is low because the electrons are not bound by chemical reactions. This lack of chemical bonding also implies that the UC can be completely discharged, leading to larger voltage swings as a function of the state of charge (SOC).

46.2.3 Flow Batteries and Regenerative Fuel Cells (RFC)

Flow batteries, also called redox (reduction-oxidation) batteries, comprise two electrolytes, separated by ion or proton exchange membrane. Energy can be stored in the electrolytes by increasing the potential difference between the two liquids –in other words, by oxidising one and reducing the other. Alternatively, electricity can be produced by reversing the process. The oxidation/reduction process is performed by the proton exchange membrane.

Flow batteries have a number of advantages, such as easy scalability (capacity proportional to tank size, whereas power output is proportional to PEM surface area), no detrimental effects of a deep discharge, very low self-discharge, low cost for a large system compared to batteries, and long cycle life. In contrast, the energy and power densities are quite low and the system is complex, requiring pumps and plumbing to circulate the electrolyte through the membrane. Therefore, this technology has found commercial application only for large-scale storage such as utility applications [3, 4].

Three types of flow batteries have shown commercial promise: vanadium redox, polysulfide bromide, and zinc bromide. Vanadium redox has the added advantage of using the same material for both electrolytes, removing the threat of cross-contamination through the PEM. Polysulfide bromide and zinc bromide use bromide, presenting the threat of releasing the highly toxic bromine gas [4].

Regenerative fuel cells (or unitized regenerative fuel cells) are sometimes grouped in with flow batteries, as the power-producing process is quite similar. Fuel cells consume hydrogen and oxygen to produce water and electricity. Unitized regenerative fuel cells are also able to function to separate water back into hydrogen and oxygen. The hydrogen is then stored as hydrogen gas or as methanol for future use, to generate electricity. Current research aims to use PEM-type fuel cells, with hydrogen or methanol as the main storage. The issue is to design a system that is efficient in both directions –in fact, current unitized fuel cells are less efficient in hydrogen production than other methods, such as conventional electrolysis.

46.2.4 Fuel Cells (FC)

A fuel cell is typically similar in operation to a conventional battery, although it has some distinct physical differences. Primarily, a fuel cell is an electrochemical device wherein the chemical energy of a fuel is converted directly into electric power [5]. The main difference between a conventional battery and a fuel cell is that, unlike a battery, a fuel cell is supplied with reactants externally. As a result, whereas a battery is discharged, a fuel cell never faces such a problem as long as the supply of fuel is provided. As depicted in Fig. 46.1, electrodes and electrolyte are the main parts of a fuel cell. The most popular type of fuel cell is the hydrogen-oxygen fuel cell.

FIGURE 46.1 Typical diagram of a fuel cell.

As shown in Fig. 46.1, hydrogen is used as the fuel to be fed to the anode. The cathode, in contrast, is fed with oxygen, which may be acquired from air. The hydrogen atom is split up into protons and electrons, which follow different paths, but ultimately meet at the cathode. For the splitting-up process, we need to use a suitable catalyst. The protons take up the path through the electrolyte, whereas the electrons follow a different external path of their own. This, in turn, facilitates a flow of current, which can be used to supply an external electric load. The electrode reactions are given as follows:

Anode:2H₂ → 4H⁺ + 4e⁻

Cathode: O₂ + 4e⁻ → 2O²⁻

Overall reaction: 2H₂ + O₂ → 2H₂O

From these simple and basic expressions describing the operation of a typical fuel cell, it is clear that there exists no combustion and hence no production of emissions. This makes the fuel cell environmentally suitable.

A typical i –v curve of fuel cells is shown in Fig. 46.2. The output voltage decreases as the current increases. Moreover, the efficiency of a fuel cell is defined as the ratio of electrical energy generated to the input hydrogen energy. Generally, cell efficiency increases with higher operating temperature and pressure [5].

FIGURE 46.2 Typical i –v curve of a fuel cell.

Fuel cells have many favorable characteristics for energy conversion. As explained earlier, they are environmentally acceptable due to a reduced value of carbon dioxide (CO₂) emission for a given power output. Moreover, the usage of fuel cells reduces transmission losses, resulting in higher efficiency.

Typical values of efficiency range between 40 and 85%. Another advantage of fuel cells is their modularity. They are inherently modular, which means they can be configured to operate with a wide range of outputs, from 0 to 50 MW, for natural gas fuel cells, to 100 MW or more, for coal gas fuel cells. Another unique advantage of fuel cells is that hydrogen, which is the basic fuel used, is easily acquirable from natural gas, coal gas, methanol, and other similar fuels containing hydrocarbons. Finally, the waste heat/exhaust can be utilized for cogeneration and for heating and cooling purposes. This exhaust is useful in residential, commercial, and industrial cogeneration applications. Basically, for cogeneration, the fuel cell exhaust is used to feed a mini- or a microturbine generator unit. These turbines are generally gas turbines. Because the waste thermal energy is recovered and converted into additional electrical energy, the overall system efficiency is improved. The gas turbine fulfills this role suitably. The typical sizes of such systems range from 1 to 15 MW.

46.3.1 Battery Modeling

As mentioned earlier, precise battery models are required for several applications such as for the simulation of energy consumption of electric vehicles, portable devices, or for power system applications. The major challenge in modeling a battery source is the nonlinear characteristic of the equivalent circuit parameters, which require lengthy experimental and numerical procedures. The battery itself has some internal parameters, which need to be taken care of [6]. In this section, three basic types of battery models will be presented: ideal, linear, and Thevenin. Finally, a simple lead acid battery model for traction applications that can be simulated in a CAD software will also be presented.

46.3.2 Electrical Modeling of Fuel Cell Power Sources

Over the past few years, there have been great environmental concerns shown with respect to emissions from vehicles. These concerns, along with the recent developments in fuel cell technology, have made room for the hugely anticipated fuel cell market [6]. Fuel cells are today being considered for applications in hybrid electric vehicles, portable applications, renewable power sources for distributed generation applications, and other similar areas where the emission levels need to be kept to a minimum.

The proton exchange membrane (PEM) fuel cell has the potential of becoming the primary power source for HEVs utilizing fuel cells. However, such fuel cell systems are large and complex and, hence, need accurate models to estimate the auxiliary power systems required for use in the HEV. In this section, the fuel cell modeling techniques will be highlighted, thus avoiding the need to build huge and expensive prototypes. To have a clearer picture, refer to Fig. 46.5, which shows the schematic of a fuel cell/battery hybrid power system.

FIGURE 46.5 Schematic of a fuel cell/battery hybrid power system.

The battery pack in Fig. 46.5 is used to compensate for the slow start-up and transient response of the fuel processor [6]. Furthermore, the battery can also be used for the purpose of regenerative braking in the HEV.

As mentioned previously, because fuel cell systems are large, complex, and expensive, designing and building new prototypes is difficult. Hence, the feasible alternative is to model the system and examine it through simulations. The fuel cell power system consists of a reformer, a fuel cell stack, and a dc/dc (buck/boost) or dc/ac power converter. The final output from the power electronic converter is in the required dc or ac form acquired from the low-voltage dc output from the fuel cell stack. An electrical equivalent model of a fuel cell power system is discussed here, which can be easily simulated using a computer simulation software.

In the electrical equivalent model, a first-order time-delay circuit with a relatively long time-constant can represent the fuel reformer. Similarly, the fuel cell stack can also be represented by a first-order time-delay circuit, but with a shorter time constant. Thus, the mathematical model of the reformer and stack is represented as:

Here, R_r C_r = τ_r is the time constant of the reformer and R_s C_s = τ_r is the time constant of the fuel cell stack. The equivalent circuit is shown in Fig. 46.6.

FIGURE 46.6 Equivalent circuit model of a fuel cell power system.

By simulating the equivalent circuit of Fig. 46.6, the system operation characteristics can be investigated. In order to achieve a fast system response, the dc/dc or dc/ac converter can utilize its short time constant for control purposes. However, eventually the fuel has to be controlled despite its long time-delay [6]. The inputs to the chemical model of a fuel cell include mass flows of air (O₂) and hydrogen (H₂), cooling water, relative humidity of oxygen and hydrogen, and load resistance. The outputs from the chemical model include temperature of the cell, power loss, internal resistance, heat output, efficiency, voltage, and total power output. Generally, in case of excess of hydrogen supply, it is recirculated in order to avoid any wastage.

46.3.3 Electrical Modeling of Photovoltaic (PV) Cells

As mentioned earlier, photovoltaic systems have been studied widely as a renewable energy source, because not only are they environment friendly, but they also have infinite energy available from the sun. Although the PV systems have the above-mentioned advantages, their study involves precise management of factors such as solar irradiation and surface temperature of the PV cell [6]. The PV cells typically show varying v –i characteristics depending on the above-mentioned factors. Figure 46.7 shows the output characteristics of a PV cell with changing levels of illumination.

FIGURE 46.7 Typical v –i characteristics of a PV cell with varying illumination levels.

As is clear from Fig. 46.7, the current level increases with increase in the irradiation level. Figure 46.8 shows the v –i curves with varying cell temperatures.

FIGURE 46.8 Typical v –i characteristics of a PV cell with varying cell temperatures.

As depicted in Fig. 46.8, the output curves for varying cell temperatures show higher voltage level as the cell temperature increases. Therefore, while modeling the PV cell, adequate consideration must be given to these two characteristics in particular.

Keeping the above-mentioned factors in mind, the electrical equivalent circuit modeling approach is proposed here. This model is basically a nonlinear distributed circuit, in which the circuit elements consist of familiar semiconductor device parameters. Eventually, running a suitable computer simulation can easily simulate this model.

The PV cell can basically be considered a current source with the output voltage primarily dependent on the load connected to its terminals [6]. The equivalent circuit model of a typical PV cell is shown in Fig. 46.9.

FIGURE 46.9 Schematic of the equivalent circuit model of a PV cell.

Suitable forward-bias (illuminated) and reverse-bias (dark) tests can be performed on the PV cell, in order to generate the v –i curves similar to those in Figs. 46.7 and 46.8. As is clear from Fig. 46.9, there are various parameters involved in the modeling of a typical PV cell. These parameters are

I_L, light-generated current (A);

I_D1, diode saturation current (A);

I_D2, additional current due to diode quality constant (A);

I_sh, shunt current (A);

R_S, cell series resistance (Ω);

I_sh, cell shunt resistance (Ω); and

I, cell-generated current (A).

The model depicted in Fig. 46.9 examines all the characteristic measurements of the p–n junction cell type. From the above circuit, the following equation for cell current can be obtained:

Here, q is the electron charge and k is the Boltzmann's constant. The voltage at the terminals of the diodes in Fig. 46.9 can be expressed as follows:

Here, β is the voltage change temperature coefficient (V/°C). For the PV cell model of Fig. 46.9, R_S and R_sh are usually estimated when the cell is not illuminated. The series resistance, R_S, represents the ohmic losses in the front surface of the PV cell, whereas the shunt resistance, R_sh, represents the loss due to diode leakage currents. Thus, these values can be approximated from the dark characteristic curve of the cell. The generated light current (I_L) is calculated by the collective probability of free electrons and holes. It can be expressed as follows:

Here, f(x) is the probability distribution function and N is the rhythm of generated electrons and holes. Once the equations of the cell model are formulated, the efficiency of the PV cell can be obtained as

A distinct advantage of such a computer model is the fact that, with a very few number of changes, it can receive data from different kinds of PV cells maintaining satisfactory results [6]. An example of such a PV model used in conjunction with a power electronic intensive system is shown in Fig. 46.10.

FIGURE 46.10 Schematic of a PV cell model-based system for simulation.

The vital part of the system, as depicted in Fig. 46.10, is the dc/dc converter. The dc/dc converter could be a boost, buck, or buck-boost converter. Although, in the system shown in Fig. 46.10, it is valid to assume a buck or buck-boost dc/dc converter, it becomes erroneous to assume usage of a boost converter. This is because the dc/dc boost converter does not make use of the full voltage range.

46.3.4 Electrical Modeling of Ultracapacitors (UCs)

Ultracapacitors (also known as double-layer capacitors) work on the electrochemical phenomenon of very high capacitance/unit area using an interface between electrode and electrolyte. Typical values of such capacitors range from 400 to 800°F and have low values of resistivity (approximately 10^{− 3}Ω-cm) [6]. These UCs operate at high-energy densities, which are commonly required for applications such as space communications, digital cellular phones, electric vehicles, and hybrid electric vehicles. In some cases, usage of a hybridized system employing a battery alongside the UC provides an attractive energy storage system, which offers numerous advantages. This is particularly due to the fact that the UC provides the necessary high-power density, whereas the battery provides the desired high-energy density. Such a hybridized model will be discussed here.

46.3.5 Electrical Modeling of Flywheel Energy Storage Systems (FESS)

Flywheels are most definitely finding numerous applications as energy storage devices in various power system configurations. Furthermore, the constant improvement in digital signal processing (DSP) and microprocessor technologies in conjunction with the recent development in magnetic material technology makes this fact a distinct possibility. A flywheel energy storage system (FESS) is advantageous in a system comprising other secondary storage devices such as batteries as it is capable of generating optimum charge/discharge profiles for specific battery characteristics [6]. This fact facilitates the exploration of the benefits for optimizing battery management.

A rotating flywheel can store mechanical energy in the form of kinetic energy based on its inertial properties. Essentially, a FESS consists of a rotor, a motor/generator system, and a suitable enclosure [6]. An example of a flywheel energy storage system used as a voltage regulator and a UPS system is shown in Fig. 46.15.

FIGURE 46.15 Typical FESS employed as voltage regulator and UPS.

The system of Fig. 46.15 essentially operates in three modes: charging, voltage regulation, and UPS. The motor/generator (M/G) set is required for energy storage purposes in the form of the inertia of the rotor. At some suitable point in the operation of the system, it retrieves this stored energy as demanded by the load. The M/G set is a high-speed device that basically operates in the motoring mode when charging the flywheel and in the generating mode when discharging it. The motor used for the M/G set could be a brushless dc motor of appropriate rating. The FESS can be easily simulated using the following equation:

Here, V_x, i_x, and E_x are the voltages, stator currents, and back EMFs for the three phases of the BLDC motor, respectively. In addition, R, L, and M are the resistance, self-inductance, and mutual inductance of the stator winding. The back EMF is directly proportional to the mechanical speed, ω_m, and the rotor angle, θ_r.

In order to electrically simulate the same flywheel energy storage system operating in conjunction with power electronic intensive systems, it is essential to derive an equivalent electrical model of the same. For this purpose, it is critical to note the important mathematical equations that describe the above system. These are as follows:

Here, v is the voltage across the motor terminals; i is the electric current through the motor; ω is the rotor speed; T_em is the electromagnetic torque imposed on the rotor; T_L is the mechanical torque imposed on the rotor by the flywheel; J_r is the equivalent moment of inertia of the rotor; J is the moment of inertia of the flywheel; and R and L are the armature resistance and self-inductance. Furthermore, a indicates the ratio of the rated voltage of the motor to its rated speed, whereas b indicates the mechanical drag coefficient. The electrical equivalent circuit generated by combining the above three equations is depicted in Fig. 46.16.

FIGURE 46.16 Electrical equivalent circuit of a flywheel energy storage system.

It is essential to note that the circuit parameters used are basically the parameters employed for the definition of the mathematical model of the FESS. Thus, Fig. 46.16 describes the FESS system in its entirety via an electrical equivalent. Again, as mentioned earlier, the task of simulating a FESS with any electrical system becomes immensely simplified because such an electrical model can be constructed in any popular electrical CAD simulation software and can be appropriately analyzed.

46.5.1 Battery State Monitoring

A good knowledge of the state of the battery is essential for meaningful energy management [20–22]. The difficulty in measuring the condition of a battery in an operating system stems from the fact that the rate and the efficiency of the chemical reaction that produces the current depend on a number of factors, including the temperature, age, and manufacturing conditions [20]. Therefore, various figures of merit have been used to define the state of the battery. Battery SOC is defined as

The issue with this metric is that the actual amount of charge is very difficult to measure. For instance, the total amount of charge that is available for utilization changes as the battery ages. Also, the capacity scatter due to manufacturing variations makes the total amount of charge hard to determine, even for a new cell.

State of health (SOH) measures the ability of a battery to store energy, source and sink high currents, and retains charge over extended periods, relative to its initial or nominal capability. This quantity is closely related to battery age and SOC.

State of function (SOF) is the capability of the battery to perform a specific duty which is relevant to the functionality of a system powered by the battery. The SOF is a function of the battery SOC, SOH, and operating temperature. For example, a new battery (high SOH) at a lower SOC, and higher operating temperature, may perform better (higher SOF) than an older battery (low SOH) at a higher SOC, and lower operating temperature.

There are a number of methods that allow for the determination of the SOC, SOH, and SOF as outlined in Table 46.2. The simplest and most commonly used method is measuring of the open-circuit voltage of the battery and relating it to the SOC (lookup table method). In a dynamic application, this method will be very imprecise when the battery is under a load.

TABLE 46.2 Summary of techniques to measure battery condition (+/–indicates whether the method is able to estimate a particular figure of merit) [23–25]

A simple equivalent circuit model that uses the cell voltage and current to estimate the open-circuit voltage can be implemented (model-based estimation). This method requires a current sensor and processing power. Depending on the complexity of the algorithm, the processor requirements range from minute to substantial. Alternatively, a comparator can be used to identify the points where the current is zero and measure only these points (voltage at zero current method).

This method introduces imprecision because the battery does not reach its equilibrium voltage for a longer period after the zero current condition. Therefore, in dynamic situations, the error becomes substantial. More complex, processor-intensive procedures can be used and give much higher precision. For example, a more complex equivalent circuit model can be used, which also uses information from impedance and resistance measurements (model, dc resistance, and impedance spectroscopy methods). Other options include the use of fuzzy logic, neural networks, or Kalman filters. Discharge test is the only certain way of determining the values of all three figures of merit. However, to administer this test, the battery needs to be removed from the application and discharged. Therefore, this method is only used for precision validation of other monitoring methods.

Ni-MH batteries present a bigger challenge for the determination of figures of merit because the voltage versus SOC plot is not linear. In fact, the voltage is almost flat throughout the 20–80% SOC range. Also, the batteries exhibit a memory effect. The most common way of determining the SOC is by current integration. However, this method does not consider charge inefficiencies or the effect of temperature. Fuzzy logic method has been used with success for monitoring Ni-MH state of charge.

46.5.2 Cell Balancing

Cell balancing is critical for systems that consist of long strings of cells in series. Because the cells are exposed to different conditions within the pack, without equalization, the individual states of charge and, therefore, cell voltages, will gradually drift apart. In the worst-case scenario, this leads to a catastrophic event such as ignition in the case of Li-ion batteries, and in the best-case scenario, this leads to the degradation of pack life. The sources of cell imbalance stem from manufacturing variance, leading to variations in internal impedance and differences in self-discharge rate. Another source of variation is the thermal differential across the pack, resulting in differing thermodynamics in the cells. Variations in the SOC can be minimized by designing a good thermal management system and with tight manufacturing controls.

The equalization methods can be considered to be active or passive. Passive methods are effective for lead acid and Ni-MH batteries which can be overcharged safely. However, overcharge equalization is only effective on a small number of cells in series, because equalization problems grow exponentially with the number of cells in series, and extensive overcharge does lead to cell degradation.

Many active methods are available ranging from minimally effective to exorbitantly expensive. Table 46.3 gives an extensive list of available cell-balancing methods. Generally, four methods of cell equalization exist that are defined by the method of current distribution: resistive (dissipative), switch (bypass method), capacitor, and transformer-based equalization. Typically, the cost and bulkiness and efficiency increase in the same order (resistive, switch-based, capacitive, and transformer-based).

TABLE 46.3 Summary of cell-balancing strategies

An example of a dissipative system is the use of dissipative resistors. Dissipative resistor in continuous mode is good for low-power application. Because the resistors are operating in continuous mode, the resistors can be small and do not need much thermal management. Another advantage of this method is the low price.

Analog current shunting is another inexpensive method of cell balancing. In this case, current is shunted around the cell in proportion to cell voltage. This system requires a comparator and a switch per cell or module. In contrast, the system is more efficient as the current is shunted rather than dissipated. This circuit has another advantage that the current could potentially be shunted both during charge and discharge, protecting the batteries from over-discharge as well as overcharge. An alternative to analog shunting is complete shunting. This system is simpler than analog shunting, as the cell is completely bypassed when the voltage reaches a certain voltage, rather than administering a PWM signal in proportion to the cell/module voltage. Dedicated buck-boost converter at each cell/module is another alternative. This system requires the use of a switch, inductor, and a diode per cell, and is only effective during charging.

Switched capacitor method uses capacitors to balance the voltage at each cell. This is achieved by having (n – 1) capacitors connected in parallel to n batteries and using capacitors to equalize the current over the two adjacent cells. Further improvements of this method consider the use of two levels of capacitors for faster equalization or only one capacitor to improve system reliability. This equalization method is advantageous for hybrid applications where the batteries are never or seldom fully charged, as the equalization takes place at any voltage and operating condition.

Another approach is to use transformers to administer the charge to the batteries, with the charger on the primary, and each cell/module as multiple secondary. Each cell will then absorb a varying current that is inversely proportional to its voltage, thus ensuring voltage equalization. The issues with this system are the bulkiness and expense associated with the transformer, as well as the complex system control, and the inability to modularize the system once it is designed.

In summary, dissipative resistors in continuous mode, buck-boost shunting, and switched capacitors are the three most effective methods for different applications. Buck-boost shunting is appropriate for either high- or low-power applications, has relatively low cost, and is simple to control. The switched-capacitor method is suitable for HEV applications because it is effective in both charging and discharging regimes.

46.6.1 Advantages and Disadvantages of Li-Ion Battery Packs for HEV/PHEV Applications

Lithium rechargeable batteries are today at the top of their wave. For instance, a 20-kWh Li-ion battery pack weighs about 160 kg (at the rate of 100–140 kWh/kg), which is acceptable for HEV applications. In contrast, current HEV nickel-metal hydride (Ni-MH) batteries weigh between 275 and 300 kg for the same application. Moreover, Li-ion batteries also depict excellent power densities (400–800 W/kg), allowing more than 2C discharge rate (at the rate of 40–80 kW peak power in a 20-kWh pack) [26]. However, they also have many drawbacks. One of the drawbacks is the cost (projected at about $ 250–$ 300/kWh), which is the most expensive of all chemistries [26]. Another drawback is that lithium is a very flammable element, whereby its flame cannot be put off with a normal ABC extinguisher. Finally, Li-ion batteries have a cycle life between 400 and 700 cycles, which does not satisfy HEV expectations. Therefore, finding a solution to these issues is crucial.

In order to resolve the safety issue, some manufacturers have modified the chemistry of the battery to the detriment of capacity and cost. Others have developed chemistries that improve the cycle life and the calendar life to the detriment of capacity and power availability. In summary, an overall success in all the aspects has not been achieved for the moment [26].

With reference to cycle life, the battery can suffer significant degradation in its capacity, depending on its usage. Furthermore, the internal resistance also increases with each charge cycle. Also, according to the chemistry and the quality of the cells, a battery typically loses about 20% of its initial capacity after about 200–1000 full cycles, also known as the 100% DOD (depth of discharge) cycles. The cycle life can be greatly increased by reducing DOD and by avoiding complete discharges of the pack between recharging or full charging. Consequently, a significant increase is obtained in the total energy delivered, whereby the battery lasts longer. In addition, overcharging or over-discharging the pack also drastically reduces the battery lifetime.

An alternative way to solve the above-mentioned problems, which are essentially common to the all lithium rechargeable batteries, is using electronic control in the form of cell voltage equalizers. Few of the control rationales are briefly listed next.

Although these protection functionalities are useful, they prove to be highly insufficient. In fact, the differences in capacity and internal resistance from cell to cell, within the same pack, may result in unwanted voltage peaks, especially during the final stages of charge and discharge. Consider a battery pack of 14.4V (4 cells, of 3.6 V each) normally charging at 16.8 V (4 × 4.2 V). Due to the differences among the cells, the smaller capacity cell ends up with a voltage higher than the average. Consequently, if the total voltage is 16.8 V at the end of the charging cycle, the cell voltage distribution might be 4.3 V + 4.2 V + 4.2 V + 4.1V = 16.8 V, where 4.3 V corresponds to the smaller capacity cell and 4.1 V corresponds to the larger capacity cell. Depending on the protection circuitry, this situation may or may not be detected, and the resistive equalizer gradually downgrades the voltage from 4.3 to 4.2 V. The net result is a considerable downgrade in overall capacity, considering that the overvoltage occurs in the smaller capacity cell, and that this cell is later discharged by a specific amount, in order to draw level with the other cells.

In contrast, during discharge, if the lower cut-off voltage is 3 V per cell, the pack will discharge up to 12 V. As the lower capacity cell discharges faster than the rest of the cells, the voltage distribution might be 2.7V + 3 V + 3 V + 3.3 V = 12 V. Again, in this case, the lower capacity cell suffers from an over-discharge, which is not detected by the protection circuit. Thus, the cell incurs an additional capacity reduction due to the resultant over-voltage and under-voltage, which downgrade the capacity of the entire pack.

46.6.2 Operational Characteristics of Classic and Advanced Power Electronic Cell Voltage Equalizers

A battery cell voltage equalizer is an electronic controller that takes active measures to equalize the voltage in each cell. In addition, by some more complex methods, such as measuring the actual capacity and internal resistance of each cell, it equalizes the DOD of each cell. As a result, each of the cells will have the same DOD during charging and discharging, even in conditions of high dispersion in capacity and internal resistance. This causes each cell of the pack to act as an average cell. In the example presented in the previous section, instead of 282 cycles, the pack would last 602 cycles, an increment of more than 100% in the cycle life. For the same application, the requirement of current though the equalizer at a discharge of 50 A, over a 100-Ah pack, would be 6-A drain/source, over the extreme capacity cells (the ones with bigger and smaller capacity), and a total transferred power of 350 W (in the entire chain), over the complete charging/discharging time. In addition to the increment in cycle time, depending on the internal resistance of each cell, the equalizer also has the potential to improve the output power. This requires a detailed analysis of the internal resistance versus DOD, in order to have precise improvement. In the following analyses of various equalizers, it will be realized that only a few of them are capable of accomplishing this requirement.

In principle, there exist three basic families of equalizers: resistive, capacitive, and inductive. Resistive equalizers simply burn the excess power in higher voltage cells, as depicted in Fig. 46.18. Consequently, it is the cheapest option and is widely utilized for laptop batteries. As is obvious, due to inherent heating problems, resistive equalizers tend to have low equalizing currents in the range 300–500 mA and work only in the final stages of charging and flotation.

FIGURE 46.18 Schematic of atypical resistive equalizer.

In contrast, capacitive equalizers use switched capacitors, as shown in Fig. 46.19, in order to transfer the energy from the higher voltage cell to the lower voltage cell. It switches the capacitor from cell to cell, allowing each cell to physically have the same voltage. Besides, it also depicts higher current capabilities than a resistive equalizer. At the same time, the main drawback of capacitive equalizers is that it cannot control inrush currents, when big differences in cell voltages exist. In addition, it does not allow any desired voltage difference, for example, when equalizing DOD.

FIGURE 46.19 Schematic of a typical capacitive equalizer.

Finally, inductive or transformer-based equalizers use an inductor to transfer energy from the higher voltage cell to the lower voltage cell. In fact, this is the most popular family of high-end equalizers, and because of its capability to fulfill most of the needs expressed above, it is explored in more detail in the following sections.

46.7.1 Hybrid Electric and Plug-in Hybrid Electric Vehicles (HEV/PHEV)

It is an obvious fact that future vehicles are moving toward more electrification. It is widely agreed that more electric vehicles will depict major benefits over conventional vehicles in terms of improved performance, less harmful emissions, and higher drive train efficiency. Since the legislation of strict ultralow-emission standards by California Air Resource Board (CARB) in 1990, auto industries and research laboratories around the world are pursuing electric and hybrid electric vehicle research seriously. Motivation of auto manufacturers toward more electric and hybrid electric vehicles (HEVs) increased in 1993, by declaring the historic partnership program for next generation vehicles (PNGV) between the big three automakers (GM, Ford, and Chrysler) and the U.S. government.

Primarily, a hybrid electric vehicle improves total overall drive train efficiency over a standard drive system by supplying electric energy from an electric energy storage system to assist the main power source and reusing braking energy that would otherwise be lost. High-quality energy storage system (ESS) is one of the most crucial components that affects vehicles’ performance characteristics. The energy storage device charges, during low-power demands, and discharges, during high-power demands. Thus, it basically acts as a catalyst for providing an energy boost. Therefore, the engine ideally operates at its most efficient speed. Because of this intended operation, the energy storage device is sometimes referred to as the load-leveling device.

The most important traits that customers look for in the vehicles loaded by LLDs are acceleration rate, fuel economy, level of maintenance, safety, and cost [27]. All these requirements need to be supported by an efficient, fast responding, and high-capacity ESS. Therefore, improved energy storage devices are a key technology for next generation HEVs.

The introduction of large battery packs in advanced vehicles presents a major shift in how batteries are used; the profile is truly unique and varies greatly depending on the vehicle in question. In this section, typical battery load profiles are investigated in advanced vehicles. Depending on the battery usage, various battery designs are better suited for the application. In some cases, high-power batteries are required, whereas in other cases, high-energy density batteries are more appropriate. A number of simulations were performed to demonstrate the requirements from the batteries as a function of the application. The vehicles considered are the following:

The parameters of the simulated vehicles are given in Table 46.4, power-train specifications in Table 46.5, and the battery pack parameters in Table 46.6.

TABLE 46.4 Chassis specifications

TABLE 46.5 Power-train specifications

TABLE 46.6 Battery specifications

Note that the batteries are sized in accordance to the type of vehicle and the targeted all-electric range. The battery voltage was assumed to be 314 V, and the battery capacity was varied to achieve the total battery capacity required. This is equivalent to connecting strings of batteries in parallel. Battery pack specifications were chosen to be 60 Wh/kg (energy density) and 375 W/kg (power density). These specifications are well within what is achievable practically. The energy density is defined at the 1C rate, and the power is defined by the HPPC test at 20% DOD. The driving cycle is the urban dynamometer driving schedule (UDDS), representing typical urban driving. The vehicle is driven over 30 miles (four UDDS cycles), representing a typical daily commute.

Based on the parameters enlisted in Tables 46.4-46.6, the vehicles were simulated using the Advanced Vehicle Simulator (ADVISOR) software. Figure 46.24 shows simulation results for two electric vehicles with a 50-mile (EV50) and 100-mile (EV100) electric range. For each vehicle, the battery pack size was increased until the driving range reached 50 and 100 miles respectively. Because we are concerned with the battery operation, we will compare the current outputs out of the batteries, and the currents are normalized to the battery 1C rate to more easily compare the relative stresses on the battery. In the case of EV50, the currents reach a 2C rate quite often, whereas in the case of EV100, the peak current is about 1C. This stresses the need for different battery designs for the two vehicles. For EV50, the designer must chose a battery capable of supplying and absorbing a 2C rate without affecting battery life. For EV100, the designer can opt for a very high energy density battery as only 1C rate will be required. A higher density battery would in turn extend vehicle range due to the smaller vehicle mass.

FIGURE 46.24 EV50 and EV100 simulation results (from top to bottom): drive cycle, state of charge, EV50 current, normalized to the battery Crate, EV100 current, normalized to the battery Crate.

Another issue that has to be considered for EVs and PHEVs is the recharge time of the battery. If the battery pack is designed for a maximum current of 1C, it would take over an hour to charge the battery. This may not be acceptable to the user in some cases.

In the next test, HEVs are considered, as shown in Fig. 46.25. Here, three cases are investigated: Parallel HEV, Thermostat Series HEV, and Load-Following Series HEV. The Parallel HEV uses the electrical system to assist the engine with vehicle acceleration and to propel the vehicle at low speeds where the engine operation is inefficient. The state of charge of the vehicle is kept close to the target value of 50%. As the electrical system is small, the batteries provide a relatively small portion of the total vehicle power. The batteries supply currents up to 5C, and the total energy demand from the battery is also very small. Therefore, a high specific power battery would be ideal for this application, and even ultracapacitors maybe considered, as the energy throughput is minimal.

FIGURE 46.25 Parallel HEV, thermostat series HEV, and load following series HEV (from top to bottom): drive cycle, state of charge, parallel HEV current, normalized to the battery Crate, thermostat series HEV current, normalized to the battery Crate, load following series HEV current, normalized to the battery Crate.

The second case is the thermostat series hybrid. Here, the internal combustion engine is only operated at its most efficient point. The internal combustion engine is turned on when the battery state of charge reaches the minimum allowed (in this case, 45%) and is turned off when the battery state of charge reaches the maximum value (in this case, 55%). Such a control system is very demanding on the battery; in this simulation, the currents are shuffled at a IOC rate. Therefore, a practical implementation of this system would require a larger battery pack to reduce peak currents.

Finally, in the load-following series hybrid, the internal combustion engine tries to follow the road load as closely as possible, while still optimizing the use of the internal combustion engine to minimize fuel consumption. In this vehicle, the current usage drops as compared to the series thermostat. Note that the battery use in a fuel cell vehicle would be the same as in a series hybrid. If the load-following control strategy is implemented, the fuel cell is stressed more as its operating point changes, while for the thermostat control the battery pack is stressed more.

Recently, plug-in hybrids have received a great deal of attention. These vehicles act as a hybrid vehicle, where the battery pack can be recharged via the grid to supply some all-electric range. In these vehicles, the battery pack is discharged from a full charge to some target state of charge, where the vehicle is then operated as a regular hybrid. In simulations, as shown in Fig. 46.26, the target SOC is chosen to be 40%, as this value makes the most of the all-electric range, while ensuring that the life of the battery pack is not compromised by over-discharge.

FIGURE 46.26 Series PHEV10, PHEV20, and PHEV30 (from top to bottom): drive cycle, state of charge, series PHEV10 current, normalized to the battery Crate, series PHEV20 current, normalized to the battery Crate, series PHEV30 current, normalized to the battery Crate.

Three vehicles are considered in this study, PHEV10, PHEV20, and PHEV30, which give a 10-, 20-, and 30-mile all-electric range, respectively. The vehicle of choice is the series hybrid, as it is capable of all-electric operation, wherein all of the propulsion power comes from the electric motor. As is clear, the C-rates are substantial on the PHEV10 and decrease for PHEV20 and PHEV30. PHEV10 proposes an interesting power versus energy density problem, where both the power and the energy density must be high. In contrast, as the all-electric range of the vehicle increases, high specific energy is critical.

46.7.2 Fuel Cells for Automotive and Renewable Energy Applications

For automotive applications, proton exchange membrane fuel cells (PEMFCs) appear to be most suitable compared to other fuel cell technologies, such as alkaline fuel cells (AFC) or solid oxide fuel cells (SOFC). This is due to the fact that the PEMFC working conditions at low temperature allow the system to start up faster than with those technologies using high-temperature fuel cells. Moreover, the solid state of their electrolyte (no leakages and low corrosion) and their high power density make PEMFCs extremely convenient for transport applications [28]. PEMFCs also provide a very good tank-to-wheel efficiency compared to heat engines. At the same time, PEMFCs need a great deal of auxiliary equipment as shown in Fig. 46.27.

FIGURE 46.27 Proton exchange membrane (PEM) fuel cell system.

Automotive fuel cell technology continues to make substantial progress. However, fuel cell vehicles (FCVs) have not yet proven to be commercially viable nor have they been proven to be efficient. More recently, technological and engineering advancements have improved, simplified, and even eliminated components of the fuel cell system. The technical challenges and objectives for fuel cell systems in transportation applications have been well highlighted by the U.S. Department of Energy (DOE). Cost and durability are the major challenges for fuel cell systems. Air, thermal, and water management for fuel cells are also key issues. Power density and specific power are now approaching set targets. However, further improvements are needed to meet packaging requirements of commercial systems. The objective, by 2010, is to develop a 60% peak-efficient, durable, direct hydrogen fuel cell power system (including all auxiliaries) for transportation at a cost of $ 45/kW and, by 2015, at a cost of $ 30/kW, to become competitive with conventional internal combustion engine vehicles.

Another critical issue with fuel cells is their start-up times as well as operating temperatures. More recently developed fuel cell systems have been able to start and operate in temperatures ranging between –40°C and + 40°C. In these temperature conditions, start-up times of up to 50% of the rated power have been depicted: 30 s at –20°C and 5 s at 20°C. However, the size and the weight of current fuel cell systems have to be reduced drastically to meet the automotive compactness requirements, which apply both for the fuel cell stack and for auxiliary components such as the compressor, expander, humidifiers, pumps, sensors, and hydrogen storage [28]. The power mass density and the power volume density requirements for the fuel cell system are 650W/kg, 650 W/L, and 2000 W/kg or 2000 W/L, for the stack itself. The transient response of the stack is also a key issue and depends mainly on the air supply system inertia. Ideally, the transient response from 10 to 90% of the maximum power should be less than 1 s.

The hydrogen fuel is stored on-board and is supplied by a hydrogen production and fuelling infrastructure. For other applications (such as for distributed stationary power generation), hydrogen can be fuelled with reformate, produced from natural gas, liquefied petroleum gas, or renewable liquid fuels. For portable electronic devices in small equipment, methanol, and sometimes hydrogen, is the fuel of choice, using microfuel cell systems.

The objectives of hydrogen storage are the volume, weight, cost, durability, cycle life, and transient performance. On-board hydrogen storage solutions are summarized in Fig. 46.28. Some of the popular storage systems include high-capacity metal hydrides, high-surface area sorbents, chemical hydrogen storage carriers, low-cost and conformable tanks, compressed/cryogenic hydrogen tanks, and new materials or processes, such as conducting polymers, spillover materials, metal organic frameworks (MOFs), and other nanostructured materials. In general, there are two principal types of onboard storage systems. (1) On-board reversible systems, which can be refueled on-board the vehicle from a hydrogen supply at the fueling station. Compressed/cryogenic tanks, some of the metal hydrides, and high-surface area sorbents represent these solutions. (2) Regenerative off-board systems, which involve materials that are not easily refilled with hydrogen, while on-board the vehicle. These solutions include chemical hydrogen storage materials and some metal hydrides, where temperature, pressure, kinetics, and/or energy requirements are such that the processes must be conducted off-board the vehicle [28].

FIGURE 46.28 State-of-the-art hydrogen storage technologies and DOE system targets.

A majority of FCVs that are being proposed more recently use 350-bar hydrogen tanks, which have system gravimetric and volumetric capacities of 2.8–3.8% weight and 17–18 g/L, respectively. Cryo-compressed hydrogen and liquid hydrogen systems are also fast approaching U.S. DOE targets, as shown in Fig. 46.28. However, these solutions are still not affordable for mass production, as other requirements such as cost, hydrogen charging/discharging rates, and durability are also key issues for hydrogen storage. Liquid hydrogen storage is being demonstrated as workable, but with limitations. It provides both higher gravimetric and volumetric density advantages over compressed gas storage, but depicts issues with boil off and dealing with cryogenic liquids. Hence, it is not likely to be widely accepted by automobile manufacturers.

A more practical application for fuel cells is distributed generation (DG) power plants. The popular choices for DG are Phosphoric Acid FC, Molten Carbonate FC, Solid Oxide FC, and the Proton Exchange Membrane FC. Their applications in DG are briefly discussed here.

46.7.3 Fuel-Cell-Based Hybrid DG Systems

Individual fuel cell units ranging from 3 to 250 kW can be used in conjunction with high-speed microturbines, for high-power DG applications. The other popular DG technology is the PV power generation system, which is suited to provide up to 250 kW of power. These topologies are discussed in detail here.