Energy sources and multi-input DC-DC converters used in hybrid electric vehicle applications – A review

With the drastic inclination towards reduction of atmospheric issues, hybrid electric vehicles are becoming the major alternative for internal combustion engine vehicles. Compared to internal combustion engine vehicles, hybrid electric vehicles are remarkable in terms of efficiency, durability and acceleration capability. However, the major drawback of hybrid electric vehicle is energy storage capability. An electric vehicle requires the energy sources with high specific power (W/kg) and high specific energy (Wh/kg) to reduce the charging time. Generally, fuel cells, batteries, ultracapacitors, flywheels and regenerative braking systems are used in hybrid electric vehicles as energy sources and energy storage devices. All these energy storage devices are connected to the different DC-DC converter topologies to increase the input source voltage. From the recent past, most of the hybrid electric vehicles are using multi-input converters to connect more than one energy source in order to improve the efficiency and reliability of the vehicle. This survey presents an assessment of present and future trend of energy storage devices and different multi-input DC-DC converter topologies that are being used in hybrid electric vehicles. In addition, different electric vehicle architectures are also discussed.     

System design and control strategy of the vehicles using hydrogen energy

This paper presented a system design review of fuel cell hybrid vehicle. Fuel supply, hydrogen storage, DC/DC converters, fuel cell system and fuel cell hybrid electric vehicle configurations were also reviewed. We explained the difference of fuel supply requirement between hydrogen vehicle and conventional vehicles. Three different types of hydrogen storage system for fuel supply are briefly introduced: high pressure, liquid storage and metal oxides storage. Considering of the potential risk of explosion, a security hydrogen storage system is designed to restrict gas pressure in the safe range. Due to the poor dynamic performance of fuel cells, DC/DC converters were added in hybrid vehicle system to improve response to the changes of power demand. Requirements that in order to select a suitable DC/DC converter for fuel-cell vehicles design were listed. We also discussed three different configurations of fuel-cell hybrid vehicles: “FC + B”, “FC + C”, and “FC + B + C”, describing both disadvantages and advantages. “FC + B + C” structure has a better performance among three structures because it could provide or absorb peak current during acceleration and emergency braking. Finally, the energy management strategies of fuel cell and were proposed and the automotive energy power requirement of an application example was calculated.     

An improved energy management strategy for FC/UC hybrid electric vehicles propelled by motor-wheels

The hybridization of the fuel-cell electric-vehicle (FCEV) by a second energy source has the advantage of improving the system's dynamic response and efficiency. Indeed, an ultra-capacitor (UC) system used as an energy storage device fulfills the FC slowest dynamics during fast power transitions and recovers the braking energy. In FC/UC hybrid vehicles, the search for a suitable power management approach is one of the main objectives. In this paper, an improved control strategy managing the active power distribution between the two energy sources is proposed. The UC reference power is calculated through the DC link voltage regulation. For the FC power demand, an algorithm with five operating modes is developed. This algorithm, depending on the UC state of charge (SOC) and the vehicle speed level, minimizes the FC power demand transitions and therefore ameliorates its durability. The traction power is provided using two permanent magnetic synchronous motor-wheels to free more space in the vehicle. The models of the FC/UC vehicle system parts and the control strategy are developed using MATLAB software. Simulation results show the effectiveness of the proposed energy management strategy.     

A wavelet-fuzzy logic based energy management strategy for a fuel cell/battery/ultra-capacitor hybrid vehicular power system

Due to increasing concerns on environmental pollution and depleting fossil fuels, fuel cell (FC) vehicle technology has received considerable attention as an alternative to the conventional vehicular systems. However, a FC system combined with an energy storage system (ESS) can display a preferable performance for vehicle propulsion. As the additional ESS can fulfill the transient power demand fluctuations, the fuel cell can be downsized to fit the average power demand without facing peak loads. Besides, braking energy can be recovered by the ESS. This study focuses on a vehicular system powered by a fuel cell and equipped with two secondary energy storage devices: battery and ultra-capacitor (UC). However, an advanced energy management strategy is quite necessary to split the power demand of a vehicle in a suitable way for the on-board power sources in order to maximize the performance while promoting the fuel economy and endurance of hybrid system components. In this study, a wavelet and fuzzy logic based energy management strategy is proposed for the developed hybrid vehicular system. Wavelet transform has great capability for analyzing signals consisting of instantaneous changes like a hybrid electric vehicle (HEV) power demand. Besides, fuzzy logic has a quite suitable structure for the control of hybrid systems. The mathematical and electrical models of the hybrid vehicular system are developed in detail and simulated using MATLAB^®, Simulink^® and SimPowerSystems^® environments.     

A power allocation strategy of a hybrid energy storage system for a PV grid-connected system

针对光伏并网系统中光伏微电源出力的波动性和间歇性,将蓄电池和超级电容器构成的混合储能系统HESS（hybrid energy storage system）应用到光伏并网系统中可以实现光伏功率平滑、能量平衡以及提高并网电能质量。在同时考虑蓄电池的功率上限和超级电容的荷电状态（SOC）的情况下,对混合储能系统提出了基于超级电容SOC的功率分配策略;该策略以超级电容的SOC和功率分配单元的输出功率作为参考值,对混合储能系统充放电过程进行设计。超级电容和蓄电池以Bi-direction DC/DC变换器与500 V直流母线连接,其中超级电容通过双闭环控制策略对直流母线电压进行控制。仿真结果表明,所提功率分配策略能对混合储能系统功率合理分配,而且实现了单位功率因数并网,稳定了直流母线电压。     

Energy management of fuel cell/battery/ultracapacitor in electrical hybrid vehicle

This paper describes an energy management algorithm for an electrical hybrid vehicle. The proposed hybrid vehicle presents a fuel cell as the main energy source and the storage system, composed of a battery and a supercapacitor as the secondary energy source. The main source must produce the necessary energy to the electrical vehicle. The secondary energy source produces the lacking power in acceleration and absorbs excess power in braking operation. The addition of a supercapacitor and battery in fuel cell-based vehicles has a great potential because it allows a significant reduction of the hydrogen consumption and an improvement of the vehicle efficiency. Other the energy sources, the electrical vehicle composed of a traction motor drive, Inverter and power conditioning. The last is composed of three DC/DC converters: the first converter interfaces the fuel cell and the DC link. For the second and the third converter, two buck boost are used in order to interface respectively the ultracapacitor and the battery with the DC link. The energy management algorithm determines the currents of the converters in order to regulate accurately the power provided from the three electrical sources. This algorithm is simulated with MATLAB_Simulink and implemented experimentally with a real-time system controller based on dSPACE. In this paper, the proposed algorithm is evaluated for the New European Driving Cycle (NEDC). The experimental results validate the effectiveness of the proposed energy management algorithm.     

Neural network-based energy management of multi-source (battery/UC/FC) powered electric vehicle

Due to increased environmental pollution and global warming concerns, the use of energy storage units that can be supported by renewable energy resources in transportation becomes more of an issue and plays a vital role in terms of clean energy solutions. However, utilization of multiple energy storage units together in an electric vehicle makes the powertrain system more complex and difficult to control. For this reason, the present study proposes an advanced energy management strategy (EMS) for range extended battery electric vehicles (BEVs) with complex powertrain structure. Hybrid energy storage system (HESS) consists of battery, ultra-capacitor (UC), fuel cell (FC) and the vehicle is propelled with two complementary propulsion machines. To increase powertrain efficiency, traction power is simultaneously shared at different rates by propulsion machines. Propulsion powers are shared by HESS units according to following objectives: extending battery lifetime, utilizing UC and FC effectively. Primarily, to optimize the power split in HESS, a convex optimization problem is formulated to meet given objectives that results 5 years prolonged battery lifetime. However, convex optimization of complex systems can be arduous due to the excessive number of parameters that has to be taken into consideration and not all systems are suitable for linearization. Therefore, a neural network (NN)-based machine learning (ML) algorithm is proposed to solve multi-objective energy management problem. Proposed NN model is trained with convex optimization outputs and according to the simulation results the trained NN model solves the optimization problem within 92.5% of the convex optimization one.     

An experimental study of a PEM fuel cell power train for urban bus application

An experimental study was carried out on a fuel cell propulsion system for minibus application with the aim to investigate the main issues of energy management within the system in dynamic conditions. The fuel cell system (FCS), based on a 20 kW PEM stack, was integrated into the power train comprising DC–DC converter, Pb batteries as energy storage systems and asynchronous electric drive of 30 kW. As reference vehicle a minibus for public transportation in historical centres was adopted. A preliminary experimental analysis was conducted on the FCS connected to a resistive load through a DC–DC converter, in order to verify the stack dynamic performance varying its power acceleration from 0.5 kW s⁻¹ to about 4 kW s⁻¹. The experiments on the power train were conducted on a test bench able to simulate the vehicle parameters and road characteristics on specific driving cycles, in particular the European R40 cycle was adopted as reference. The “soft hybrid” configuration, which permitted the utilization of a minimum size energy storage system and implied the use of FCS mainly in dynamic operation, was compared with the “hard hybrid” solution, characterized by FCS operation at limited power in stationary conditions. Different control strategies of power flows between fuel cells, electric energy storage system and electric drive were adopted in order to verify the two above hybrid approaches during the vehicle mission, in terms of efficiencies of individual components and of the overall power train.     

Coordinated power control with virtual inertia for fuel cell-based DC microgrids cluster

This paper proposes a coordinated power control method with virtual inertia (VI) for fuel cell-based DC microgrids (MGs) cluster based on the multi-agent system (MAS) control frame. In the primary control layer, a local energy management strategy with virtual inertia is adopted to suppress the bus voltage disturbance, smooth the output power of fuel cell, as well as manage the power flow in the DC MG. In the secondary and tertiary control layers, a coordinated power control method based on MAS frame is implemented for the power flow among the sub-MGs. More specifically, the secondary voltage control loop is used for the bus voltage smooth control at the moment of microgrids interconnection, and the power flow tertiary control regular is applied for the battery SoC converge uniformly in finite time. Also, a fuel cell-based DC microgrids cluster real-time simulation platform is established to verify the control performance of the proposed coordinated power control method on the bus voltage smooth control, the SoC consistency control, load abrupt response and ‘plug and play’ capability.     

Decentralized coordination control of PV generators,storage battery,hydrogen production unit and fuel cell in islanded DC microgrid

Renewable energy sources (RESs) have been limited to connect to main grid because of their inherent disadvantages such as the fluctuation and intermittence of the output power, the inconsistency with load curve and the impact on the relay protection. Hydrogen production unit (HPU) can address the above issues because it can achieve large-capacity and long-term power absorption, and requires not much of the RESs. In this paper, an adaptive coordination control strategy is proposed in the islanded DC microgrid containing PV generators, storage battery, fuel cell and HPU. As for HPU, the energy conversion efficiency from electric energy to hydrogen energy of HPU is derived and it reveals that there exists a peak value in the efficiency curve. Then an efficiency adaptive control is proposed to adjust the power absorption by regulating the efficiency point based on the dc bus voltage. As for storage battery, the state of charge (SoC) and the instantaneous charging and discharging power of the battery are considered, which can avoid the battery being overused or damaged. As for PV generator, the designed PV controller can adaptively regulate its output power from the maximum power point to the reference power point. As for fuel cell, it is designed that the fuel cell starts to supply power in low-SoC condition with constant power control strategy. Finally, the stability of the coordination control strategy is analyzed based on Nyquist stability criterion and the control effectiveness is verified with simulation and experimental results.     

Energy management of a hybrid energy system (PV / PEMFC and lithium-ion battery) based on hydrogen minimization modeled by macroscopic energy representation

This research work is designed for the management of the electric power of an autonomous hybrid system which generally integrates several subsystems, whose main source of production is solar energy (photovoltaic panels) coupled with a hydrogen fuel cell using a storage device (lithium battery).This energy coupling behavior is used in a wide range of operating conditions ensuring the originality of the exploitation of the energy produced to supply electricity to remote regions and isolated urban regions of southern Algeria, which will be modeled by a recent graphic formalism methodology macroscopic energy representation and controlled by a simple method the maximum control structure that takes into account all the inputs and outputs of the system. This hybrid system is controlled by an energy management strategy by acting on a common continuous bus with variable residential load via a DC/DC converter, allowing control of the amount of energy between the different energy resources to minimize the use of the fuel cell from which to minimize hydrogen consumption. Another is used to maintain the voltage of this bus at its reference via the battery by regulating the bidirectional DC/DC converter.     

A comprehensive review on energy management strategies of hybrid energy storage system for electric vehicles

The attention on green and clean technology innovations is highly demanded of a modern era. Transportation has seen a high rate of growth in today's cities. The conventional internal combustion engine‐operated vehicle liberates gasses like carbon dioxide, carbon monoxide, nitrogen oxides, hydrocarbons, and water, which result in the increased surface temperature of the earth. One of the optimum solutions to overcome fossil fuel degrading and global warming is electric vehicle. The challenging aspect in electric vehicle is its energy storage system. Many of the researchers mainly concentrate on the field of storage device cost reduction, its age increment, and energy densities' improvement. This paper explores an overview of an electric propulsion system composed of energy storage devices, power electronic converters, and electronic control unit. The battery with high‐energy density and ultracapacitor with high‐power density combination paves a way to overcome the challenges in energy storage system. This study aims at highlighting the various hybrid energy storage system configurations such as parallel passive, active, battery–UC, and UC–battery topologies. Finally, energy management control strategies, which are categorized in global optimization, are reviewed. Copyright © 2017 John Wiley & Sons, Ltd.     

Multi-mode control strategy for fuel cell electric vehicles regarding fuel economy and durability

A proton electrolyte membrane (PEM) fuel cell system and a Li-ion battery (LIB) are two power sources in a fuel cell electric vehicle (FCEV). The fuel cell system is composed of a fuel cell stack and subsystems for air/hydrogen supply and cooling water. The operation procedure of the fuel cell system can be generally separated into several processes, e.g. starting up, normal/abnormal working and shutting down. In this paper, a multi-mode real-time control strategy for a FCEV is proposed. The strategy is established based on three typical processes (starting up, normal working, shutting down) of the fuel cell system, taking the fuel economy and system durability into consideration. The strategy is applied into a platform vehicle for the 12th 5-year project of “the next generation technologies of fuel cell city buses”. Experiments of the “China city bus typical cycle” on a test bench for the bus were carried out. Results show that, the fuel economy is 7.6 kg (100 km)⁻¹ in the battery charge-sustaining status. In a practical situation, a total driving mileage of more than 270 km can be achieved. Cycle testing also showed that, the degradation rate of the fuel cell was reduced to half of the original level. No performance degradation of the LIB system was observed in the cycling test.     

Energy management of a fuel cell hybrid ultra-energy efficient vehicle

This paper focuses on energy management in an ultra-energy efficient vehicle powered by a hydrogen fuel cell with rated power of 1 kW. The vehicle is especially developed for the student competition Shell Eco-marathon in the Urban Concept category. In order to minimize the driving energy consumption a simulation model of the vehicle and the electric propulsion is developed. The model is based on vehicle dynamics and real motor efficiency as constant DC/DC, motor controllers and transmission efficiency were considered. Based on that model five propulsion schemes and driving strategies were evaluated. The fuel cell output parameters were experimentally determined. Then, the driving energy demand and hydrogen consumption was estimated for each of the propulsion schemes. Finally, an experimental study on fuel cell output power and hydrogen consumption was conducted for two propulsion schemes in case of hybrid and non-hybrid power source. In the hybrid propulsion scheme, supercapacitors were used as energy storage as they were charged from the fuel cell with constant current of 10 A.     

Hydraulic/electric synergy system (HESS) design for heavy hybrid vehicles

Energy storage source is one of the key factors constraining the development of hybrid drive technology. Single energy storage source is difficult to satisfy the hybrid vehicle’s requirements for both energy density and power density. This paper presents a hydraulic/electric synergy system (HESS) for heavy hybrid vehicles to overcome the existing drawbacks of single energy storage source. The key components in the synergy system are sized to improve the fuel economy potential while satisfying the vehicle performance constraints. In order to achieve optimal fuel economy, energy control strategy tailored specially to the synergy system is designed to manage the power distribution between multiple energy sources based on theirs characteristics. The experiments and simulations demonstrate that the proposed synergy system can provide good fuel economy and overall system efficiency.     

A coupled power-voltage equilibrium strategy based on droop control for fuel cell/battery/supercapacitor hybrid tramway

In order to improve the robustness of the energy management system (EMS) and avoid the influence of demand power on the design of EMS, a coupled power-voltage equilibrium strategy based on droop control (CPVE-DC) is proposed in this paper. Making use of the principal that the DC bus can directly reflect the changes of load power, the proposed strategy couples DC bus voltage with output powers through droop control to achieve self-equilibrium. The proposed EMS is applied into a hybrid tramway model configured with multiple proton exchange membrane fuel cell (PEMFC) systems, batteries and super capacitors (SCs). FC systems and SC systems are responsible for satisfying most of the demand power, therefore the CPVE-DC strategy generates FCs and SCs reference power through power-voltage droop control on the primary control. Then batteries supplement the rest part of load power and generate DC bus voltage reference value of the next sampling time. With the gambling between output power and DC bus voltage, the hybrid system achieves self-equilibrium and steps into steady operation by selecting appropriate droop coefficients. Then the secondary control of the proposed strategy allocates power between every single unit. In addition, a penalty coefficient is introduced to balance SOC of SCs. The proposed strategy is tested under a real drive cycle LF-LRV on RT-LAB platform. The results demonstrate that the proposed strategy can achieve self-equilibrium and is effective to allocate demand power among these power sources,achieve active control for the range of DC bus voltage and SOC consensus of SCs as well. In addition, some faults are simulated to verify the robustness of the proposed strategy and it turns out that the CPVE-DC strategy possesses higher robustness. Finally, the CPVE-DC strategy is compared with equivalent consumption minimization strategy (ECMS) and the results shows that the proposed strategy is able to get higher average efficiency and lower equivalent fuel consumption.     

混合动力公交车深度强化学习能量管理策略研究

以某款双行星排混合动力公交车为样车,针对控制变量柴油机转速的离散控制和连续控制分别提出基于双深度Q网络(double deep Q-learning, DDQN)和基于双延迟深度确定性策略梯度(twin delayed deep deterministic policy gradients, TD3)的能量管理策略,并使用优先级经验回放对策略进行优化。运用仿真试验,研究样车在C-WTVC工况下的能量管理特性。通过与动态规划策略(dynamic programming, DP)进行对比发现：DDQN和TD3策略收敛速度快,具有较强的自适应能力;与DP策略相似,DDQN和TD3策略在控制逻辑上均表现为低速和较低转矩时纯电驱动,高速和较高转矩时混合驱动;三种策略下柴油机均主要工作于中低转速区间,且TD3策略可以对柴油机转速进行连续控制;DDQN和TD3策略的百公里油耗分别为19.51L和19.48L,燃油经济性均达到DP策略的93%,研究证明了DDQN和TD3策略的有效性。     

Dynamic behaviour of Li batteries in hydrogen fuel cell power trains

A Li ion polymer battery pack for road vehicles (48 V, 20 Ah) was tested by charging/discharging tests at different current values, in order to evaluate its performance in comparison with a conventional Pb acid battery pack. The comparative analysis was also performed integrating the two storage systems in a hydrogen fuel cell power train for moped applications. The propulsion system comprised a fuel cell generator based on a 2.5 kW polymeric electrolyte membrane (PEM) stack, fuelled with compressed hydrogen, an electric drive of 1.8 kW as nominal power, of the same typology of that installed on commercial electric scooters (brushless electric machine and controlled bidirectional inverter). The power train was characterized making use of a test bench able to simulate the vehicle behaviour and road characteristics on driving cycles with different acceleration/deceleration rates and lengths. The power flows between fuel cell system, electric energy storage system and electric drive during the different cycles were analyzed, evidencing the effect of high battery currents on the vehicle driving range. The use of Li batteries in the fuel cell power train, adopting a range extender configuration, determined a hydrogen consumption lower than the correspondent Pb battery/fuel cell hybrid vehicle, with a major flexibility in the power management.     

Prediction-based optimal power management in a fuel cell/battery plug-in hybrid vehicle

A prediction-based power management strategy is proposed for fuel cell/battery plug-in hybrid vehicles with the goal of improving overall system operating efficiency. The main feature of the proposed strategy is that, if the total amount of energy required to complete a particular drive cycle can be reliably predicted, then the energy stored in the onboard electrical storage system can be depleted in an optimal manner that permits the fuel cell to operate in its most efficient regime. The strategy has been implemented in a vehicle power-train simulator called LFM which was developed in MATLAB/SIMULINK software and its effectiveness was evaluated by comparing it with a conventional control strategy. The proposed strategy is shown to provide significant improvement in average fuel cell system efficiency while reducing hydrogen consumption. It has been demonstrated with the LFM simulation that the prediction-based power management strategy can maintain a stable power request to the fuel cell thereby improving fuel cell durability, and that the battery is depleted to the desired state-of-charge at the end of the drive cycle. A sensitivity analysis has also been conducted to study the effects of inaccurate predictions of the remaining portion of the drive cycle on hydrogen consumption and the final battery state-of-charge. Finally, the advantages of the proposed control strategy over the conventional strategy have been validated through implementation in the University of Delaware's fuel cell hybrid bus with operational data acquired from onboard sensors.     

Fuel cell and ultra-capacitor hybridization: A prototype test bench based analysis of different energy management strategies for vehicular applications

An energy storage system with sufficient power capacity should be incorporated with fuel cells (FCs) to compensate the slow dynamics of FCs. Ultra-capacitors (UCs) are potential candidates for a solution in this aspect. A test bench of such an FC/UC hybrid configuration that can emulate the dynamics of vehicular systems is presented in this paper. Namely, the test bench performance verification of wavelet transform and fuzzy logic based energy management strategy that was discussed in earlier simulation-based studies of the authors is investigated. Of equal importance is the comparison of the cascade wavelet-fuzzy logic based strategy with the case of using only fuzzy logic in the energy management is presented. Experimental results with small-scale devices, a PEMFC (5 kW, 48 V) manufactured by Plug Power^® Company, and a UC bank composed of 430 F, 16 V and 165 F, 48 V UC modules manufactured by Maxwell Technologies^® Company, illustrate the successful performance analysis of employed energy management schemes during similar motor cycles.