Jianqiu Li

Driving and braking control of PM synchronous motor based on low-resolution hall sensor for battery electric vehicle

Resolvers are normally employed for rotor positioning in motors for electric vehicles, but resolvers are expensive and vulnerable to vibrations. Hall sensors have the advantages of low cost and high reliability, but the positioning accuracy is low. Motors with Hall sensors are typically controlled by six-step commutation algorithm, which brings high torque ripple. This paper studies the high-performance driving and braking control of the in-wheel permanent magnetic synchronous motor (PMSM) based on low-resolution Hall sensors. Field oriented control (FOC) based on Hall-effect sensors is developed to reduce the torque ripple. The positioning accuracy of the Hall sensors is improved by interpolation between two consecutive Hall signals using the estimated motor speed. The position error from the misalignment of the Hall sensors is compensated by the precise calibration of Hall transition timing. The braking control algorithms based on six-step commutation and FOC are studied. Two variants of the six-step commutation braking control, namely, half-bridge commutation and full-bridge commutation, are discussed and compared, which shows that the full-bridge commutation could better explore the potential of the back electro-motive forces (EMF), thus can deliver higher efficiency and smaller current ripple. The FOC braking is analyzed with the phasor diagrams. At a given motor speed, the motor turns from the regenerative braking mode into the plug braking mode if the braking torque exceeds a certain limit, which is proportional to the motor speed. Tests in the dynamometer show that a smooth control could be realized by FOC driving control and the highest efficiency and the smallest current ripple could be achieved by FOC braking control, compared to six-step commutation braking control. Therefore, FOC braking is selected as the braking control algorithm for electric vehicles. The proposed research ensures a good motor control performance while maintaining low cost and high reliability.

The helium purification system of the HTR-10

Abstract In order to reduce the quantity of chemical impurities in the primary coolant helium and to remove the gaseous radionuclide fission products, a helium purification system mainly composed of a copper oxide bed, a molecular sieve adsorber and a low temperature adsorber is designed for the HTR-10. One actual purification train is designed for a helium flow rate of 10.5 kg h −1 , corresponding with a 5% gas change of the helium inventory in primary circuit. It is anticipated that more than 2000 h continuous purification operation will be reached between regeneration.

Analysis of the heat generation of lithium-ion battery during charging and discharging considering different influencing factors

Operating temperature of lithium-ion battery is an important factor influencing the performance of electric vehicles. During charging and discharging process, battery temperature varies due to internal heat generation, calling for analysis of battery heat generation rate. The generated heat consists of Joule heat and reaction heat, and both are affected by various factors, including temperature, battery aging effect, state of charge (SOC), and operation current. In this article, a series of experiments based on a power-type lithium manganese oxide/graphite battery was implemented under different conditions. The parameters for Joule heat and reaction heat are determined, and the Joule heat, reaction heat as well as total heat generation rate is detailed and analyzed considering the influence of temperature, aging, SOC, and current. In order to validate the accuracy of heat generation rate, a lumped battery heat transfer model is applied to calculate the temperature variation, and the estimated temperature variation shows good correspondence with experimental results under different currents and aging conditions. Due to its simplicity, the temperature variation estimation method is suitable for real time applications.

Dynamic Programming Algorithm for minimizing operating cost of a PEM fuel cell vehicle

A PEM (Proton Exchange Membrane) fuel cell city bus utilizes a PEM fuel cell engine as the primary source, and a li-ion battery system as the auxiliary power source. By optimizing the power split strategy and recycling braking energy, this kind of power-train has advantages of zero emission and high energy efficiency. However, the cost of hydrogen gas is far more expensive than that of the electric energy. How to split the power between the two power sources so as to minimize the operating cost, as well as guarantee the vehicle dynamic performance, becomes an important topic. This paper proposes a Dynamic Programming Algorithm (DPA) to solve the minimizing problem. Some details of the DPA are discussed, e.g. the principles of selecting parameters for the algorithm. The effectiveness of the algorithm is verified by comparing simulating results of different algorithms. Results show that, 1) by using the DPA algorithm, we can find the optimal control strategy in an objective way. 2) The constraints of vehicle dynamic performance on the optimal problem have great influences on the optimal results. 3) To predict the power requirement in the near future is very important to achieve an optimal real-time strategy.

Power management and economic estimation of fuel cell hybrid vehicle using fuzzy logic

Fuel cell hybrid vehicles (FCHVs) have been attracting a lot of attention as well as electric vehicles (EVs) and various hybrid electric vehicles (HEVs) for environmental issues and energy crises. One of the advantages of using foregoing vehicles is saving energy during electric motors braking regeneration. In this paper, a fuzzy logic based power management strategy considering a regenerative braking control of the electric motor is presented for proton exchange membrane (PEM) fuel cell and Nickel-Metal Hydride (Ni-MH) battery hybrid vehicular power system. The fuel economic of the FCHV is estimated by analyzing the fuel consumption of hydrogen usages. Simulation results show that the fuel economic is improved by using the proposed fuzzy logic controller for regenerative braking management.

Control strategy optimization of a hybrid fuel cell vehicle with braking energy regeneration

This paper deals with the optimized control strategy within the vehicle which is driven by a fuel cell stack hybrid with a NiMH battery. The aim is the instantaneous energy management to optimize the hydrogen consumption. At first the powertrain was modeled using data on testbed. Then the optimization control problem basing on an equivalent hydrogen consumption strategy is defined, where the motor target torque and DC/DC target current should be calculated. According to the shift signals and pedal position signals, the vehicle operation can be divided into two modes, non-brake mode (idle, drive backward, drive forward, slide) and brake mode. The optimization problem was solved respectively. Results in ldquoChina typical city bus cyclerdquo testing show the robustness and effectiveness of the strategy in improving fuel economy while maintaining drivability. The fuel economy was improved from 9.6 kg/100 km to 7.9 kg/100 km and the battery SOC was kept around 47%.

Equivalent Consumption Minimization Strategies of Series Hybrid City Buses

With ever growing concerns on energy crisis and environmental issues, alternative clean and energy efficient vehicles are favoured for public applications. Internal combustion engine(ICE)-powered series hybrid buses and fuel cell (FC) hybrid buses, respectively as a near-term and long-term strategy, have a very promising application prospect. The series hybrid vehicle utilizes an ICE/FC as the main power source and a battery/ultra capacity (UC) as the auxiliary power source. The main power source supplies the average vehicle power, and the auxiliary power source functions during accelerating and decelerating. Because the battery/UC fulfills the transient power demand fluctuations, the ICE/FC can work steadly. Thus, the durability of the fuel cell stack could be improved compared with a pure FC-powered bus in the FC series hybrid bus. And the PM and NOx can be greatly lowered in the ICE series hybrid bus compared with a traditional city bus. Besides, the ability of the energy storage source to recover braking energy enhances the fuel economy greatly. The hybrid configuration raises the question of energy management strategy, which chooses the power split between the two. The strategy is developed to achieve system-level objectives, e.g. fuel economy, low emission and battery charge-sustaining, while satisfying system constraints. Energy management strategies in the recent literature can be generally categorized into two types: rule-based strategies and optimal strategies. A rule based strategy can be easily implemented for the real-time applications based on heuristics (N.Jalil, N.A.Kheir & M.Salman, 1997). Such a strategy could be further improved by extracting optimal rules from optimal algorithms (S.Aoyagi, Y.Hasegawa & T.Yonekura, 2001). Optimal strategies differ from each other in the time range. Fuel consumption in a single control cycle is minimized in an instantaneous optimal strategy (G.Paganelli, S.Delprat & T.M.Guerra, 2002). And a global optimal strategy minimises it over a whole determined driving cycle using determined dynamic programming method (DDP) (Chan Chiao Lin et al., 2003), or over a undetermined driving cycle using stochastic dynamic programming method (SDP) (Andreas Schell et al., 2005). Other strategies minimize fuel consumption over an adaptive time span, which could be adjusted on the basis of vehicular speed, pedal 7

Instantaneous optimal regenerative braking control for a permanent-magnet synchronous motor in a four-wheel-drive electric vehicle

Recovering the kinetic energy of a vehicle is one inherent advantage of an electric vehicle. A permanent-magnet synchronous motor is widely adopted for the traction motor in an electric vehicle with the advantage of a high efficiency and a high torque density. The principle for electric braking control of the permanent-magnet synchronous motor under field-oriented control is studied. The efficiency model of the electric drive system, which is different from that of the internal-combustion engine drive system, can be exactly described by analytical equations. On this basis, the battery power can be expressed as a function of the angular velocity and the electromagnetic torque of the motor. By solving the partial differential equation for the battery power, the instantaneous optimal regenerative braking torque of the permanent-magnet synchronous motor is simply calculated according to the vehicle braking torque demand and the motor speed. Compared with the existing efficiency map method, the analytical technology is easily implemented. Then a four-wheel-drive electric vehicle is investigated to achieve optimal regenerative braking control. The dynamic behaviour of braking in the four-wheel-drive electric vehicle is also considered. The parallel braking pattern and the series braking pattern are investigated in order to evaluate the availability of braking energy recovery. The instantaneous optimal regeneration energy can be recovered for the series braking system, and a significant amount of energy can be recovered for the parallel braking system by adjusting the free travel of the brake pedal.

Rule-based fault diagnosis of hall sensors and fault-tolerant control of PMSM

Hall sensor is widely used for estimating rotor phase of permanent magnet synchronous motor(PMSM). And rotor position is an essential parameter of PMSM control algorithm, hence it is very dangerous if Hall senor faults occur. But there is scarcely any research focusing on fault diagnosis and fault-tolerant control of Hall sensor used in PMSM. From this standpoint, the Hall sensor faults which may occur during the PMSM operating are theoretically analyzed. According to the analysis results, the fault diagnosis algorithm of Hall sensor, which is based on three rules, is proposed to classify the fault phenomena accurately. The rotor phase estimation algorithms, based on one or two Hall sensor(s), are initialized to engender the fault-tolerant control algorithm. The fault diagnosis algorithm can detect 60 Hall fault phenomena in total as well as all detections can be fulfilled in 1/138 rotor rotation period. The fault-tolerant control algorithm can achieve a smooth torque production which means the same control effect as normal control mode (with three Hall sensors). Finally, the PMSM bench test verifies the accuracy and rapidity of fault diagnosis and fault-tolerant control strategies. The fault diagnosis algorithm can detect all Hall sensor faults promptly and fault-tolerant control algorithm allows the PMSM to face failure conditions of one or two Hall sensor(s). In addition, the transitions between health-control and fault-tolerant control conditions are smooth without any additional noise and harshness. Proposed algorithms can deal with the Hall sensor faults of PMSM in real applications, and can be provided to realize the fault diagnosis and fault-tolerant control of PMSM.

Advanced ECU Software Development Method for Fuel Cell Systems

The electronic control unit (ECU) in electrical powered hybrid and fuel cell vehicles is exceedingly complex. Rapid prototyping control is used to reduce development time and eliminate errors during software development. This paper describes a high-efficiency development method and a flexible tool chain suitable for various applications in automotive engineering. The control algorithm can be deployed directly from a Matlab/Simulink/Stateflow environment into the ECU hardware together with an OSEK real-time operating system (RTOS). The system has been successfully used to develop a 20-kW fuel cell system ECU based on a Motorola PowerPC 555 (MPC555) microcontroller. The total software development time is greatly reduced and the code quality and reliability are greatly enhanced.