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Continuous improvement of wind turbines represent an effective way of achieving green energy and reducing dependence on fossil fuel. Conventional lift-type horizontal axis wind turbines, which are widely used, are designed to run under high wind speed to obtain a high efficiency. Aiming to use the low-speed wind in urban areas, a novel turbine, which is called the Archimedes Spiral Wind Turbine (abbreviated as ASWT), was recently proposed for low-speed wind applications. In the current work, a numerical simulation on the five ASWT rotors with different blade angles was carried out, which were performed to predict the detailed aerodynamic performance and wake characteristics. The results show that the ASWT rotor with a large blade angle has a wider operating tip speed ratio range and a higher tip speed ratio point of maximum power coefficient within a certain range, and yet the ASWT rotor with the larger blade angle has a higher thrust coefficient. Additionally, the ASWT rotor with a large blade angle usually has a large power coefficient and thrust coefficient fluctuation amplitude. On the other hand, the ASWT rotor with a small blade angle permits the undisturbed free stream to pass through the rotor blades more easily than that with a large blade angle. This causes a stronger blockage effect for the ASWT rotor with a large blade angle. Moreover, the blade angle also has a great effect on the shape of the vortex structure. The blade tip vortex of the fixed-angle ASWT rotors is more stable than those of the variable-angle ASWT rotors. The hub vortex of the ASWT rotors with a large blade angle is stronger than those with a small blade angle. Meanwhile, the wake recovery for ASWT rotors with a small blade angle is evidently lower than those with a large blade angle. [ABSTRACT FROM AUTHOR]

With the development of fuel cell vehicle technology, an effective testing method that can be applied to develop and verify the fuel cell vehicle powertrain system is urgently required. This paper presents the X-in-the-Loop (XiL) testing method in the fuel cell vehicle (FCV) hybrid degree test to resolve the first and key issues for the powertrain system design, and the test process and scenarios were designed. The hybrid degree is redefined into the static hybrid degree for system architecture design and the dynamic hybrid degree for vehicle control strategy design, and an integrated testing platform was introduced and a testing application was implemented by following the designed testing flowchart with two loops. Experimental validations show that the sizing of the FCE (Fuel Cell Engine), battery pack, and traction motor with the powertrain architecture can be determined, the control strategy can be evaluated seamlessly, and a systematic powertrain testing solution can be achieved through the whole development process. This research has developed a new testing platform and proposed a novel testing method on the fuel cell vehicle powertrain system, which will be a contribution to fuel cell vehicle technology and its industrialization. [ABSTRACT FROM AUTHOR]

During the operation of HVDC extruded cables, voltage polarity reversal (VPR) is considered one of the most severe conditions for cable insulation. In this paper, a bipolar charge transport model developed for cylindrical geometry is improved by introducing ionic carriers from impurity dissociation for the simulation of space charge and electric field in an HVDC extruded cable with thick polymeric insulation under VPR, and the construction of the geometric model is based on a practical 160 kV DC polymeric cable. The influence of polarity reversal period (PRP) and temperature gradient (TG), formed by the load current flowing through the conductor, on the space charge evolution and the electric field distribution are investigated. The mechanisms of the charge dynamics and the field distortion affected by the PRP and the TG are also discussed. The results show that under TG, the maximum transient field appears near the interface between the conductor shield and insulation in the early stage of complete VPR. In addition, the longer the PRP, the more serious the maximum transient field distortion. Moreover, an increase in TG intensifies the maximum field distortion under steady and transient states due to the enhancement of heterocharge accumulation. [ABSTRACT FROM AUTHOR]

Due to the low efficiency and high pollution of conventional internal combustion engine vehicles, the fuel cell hybrid electric vehicles are expected to play a key role in the future of clean energy transportation attributed to the long driving range, short hydrogen refueling time and environmental advantages. The development of energy management strategies has an important impact on the economy and durability, but most strategies ignore the aging of fuel cells and the corresponding impact on hydrogen consumption. In this paper, a rule-based fuzzy control strategy is proposed based on the constructed data-driven online estimation model of fuel cell health. Then, a genetic algorithm is used to optimize this fuzzy controller, where the objective function is designed to consider both the economy and durability by combining the hydrogen consumption cost and the degradation cost characterized by the fuel cell health status. Considering that the rule-based strategy is more sensitive to operating conditions, this paper uses an artificial neural network for predictive control. The results are compared with those obtained from the genetic algorithm optimized fuzzy controller and are found to be very similar, where the prediction accuracy is assessed using MAPE, RMSE and 10-fold cross-validation. Experiments show that the developed strategy has a good generalization capability for variable driving cycles. [ABSTRACT FROM AUTHOR]

In view of the aggravation of global pollution and greenhouse effects, fuel cell electric vehicles (FCEVs) have attracted increasing attention, owing to their ability to release zero emissions. Extended-range fuel cell vehicles (E-RFCEVs) are the most widely used type of fuel cell vehicles. The powertrain system of E-RFCEV is relatively complex. Bond graph theory was used to model the important parts of the E-RFCEV powertrain system: Battery, motor, fuel cell, DC/DC, vehicle, and driver. In order to verify the control effect of energy management strategy (EMS) in a real-time state, bond graph theory was applied to hardware-in-the-loop (HiL) development. An HiL simulation test-bed based on the bond graph model was built, and the HiL simulation verification of the energy management strategy was completed. Based on the comparison to a power-following EMS, it was found that fuzzy logic EMS is more adaptive to vehicle driving conditions. This study aimed to apply bond graph theory to HiL simulations to verify that bond graph modeling is applicable to complex systems. [ABSTRACT FROM AUTHOR]

The limited lifetime of proton exchange membrane fuel cell (PEMFC) inhibits the further development of the fuel cell industry. Prediction is one of the most effective means for managing the lifetime of a fuel cell because it can assist in the implementation of mitigation actions before a vehicular fuel cell fails by estimating the residual lifetime. Therefore, this study aimed to develop a PEMFC lifetime prediction method for online applications. This paper presents the online prediction method developed for the residual lifetime of a vehicular fuel cell, which utilises data processing with an adaptive extended Kalman filter and a prediction formula. The formula considers different operating conditions and the external environment, which is in accord with the actual operating conditions of fuel cell vehicles. This method realises the online prediction of the residual lifetime of a vehicular fuel cell by updating weight coefficients for the operating conditions and environmental factors. This prediction method was validated and analysed using a simulation. The influences of key parameters on the stability and prediction accuracy of the algorithm were evaluated. The prediction method proposed in this paper can provide a reference for studies on fuel cell lifetime prediction. [ABSTRACT FROM AUTHOR]

In order to realize the low temperature and rapid cold start-up of a proton exchange membrane fuel cell stack, a dynamic model containing 40 single proton exchange membrane fuel cells is established to estimate the melting time of the proton exchange membrane fuel cell stack as well as to analyze the melting process of the ice by using the obtained liquid–solid boundary. The methods of proton exchange membrane electric heating and electrothermal film heating are utilized to achieve cold start-up of the proton exchange membrane fuel cell (PEMFC). The fluid simulation software fluent is used to simulate and analyze the process of melting ice. The solidification and melting model and multi-phase flow model are introduced. The pressure-implicit with splitting of operators algorithm is also adopted. The results show that both the proton exchange membrane electric heating technology and the electrothermal film heating method can achieve rapid cold start-up. The interior ice of the proton exchange membrane fuel cell stack melts first, while the first and 40th pieces melt afterwards. The ice melting time of the proton exchange membrane fuel cell stack is 32.5 s and 36.5 s with the two methods, respectively. In the end, the effect of different electrothermal film structures on cold start-up performance is studied, and three types of pore diameter electrothermal films are established. It is found that the electrothermal film with small holes melts completely first, and the electrothermal film with large holes melts completely last. [ABSTRACT FROM AUTHOR]

X-in-the-loop is a new vehicle development and validation method for increasingly complex vehicle systems, which integrates the driver and the environment. In view of recent developments in fuel cell electric vehicle powertrain systems, Tongji University and Karlsruhe Institute of Technology have jointly developed a set of distributed test platforms based on the X-in-the-loop approach. This platform contains models and test equipment for a fuel cell electric vehicle powertrain system. Due to the involvement of remote connection and the Internet, test with connected test benches will suffer great uncertainty cause of signal transfer delay. To figure out this uncertainty, the concept of transparency is introduced. Four parameters were selected as transparency parameters in this distributed test platform. These include vehicle speed, fuel cell output power, battery output power, and electric motor torque under several different configuration settings. With the help of transparency theory and statistical methodology, especially Analysis of Variance (ANOVA), the transparency of these four parameters was established, vehicle speed, electric motor torque, battery power, and fuel cell power are affected by network state, the degree of influence is enhanced in turn. Using new defined parametric and non-parametric methods, this paper identifies the statistical significance and the transparency limitations caused by Internet under these several configurations. These methods will generate inputs for developer setting the distributed test configuration. These results will contribute to optimize the process of geographically distributed validation and joint development. [ABSTRACT FROM AUTHOR]