Jingyu Yan

Fuzzy Control for Battery Equalization Based on State of Charge

Battery equalization, aiming at keeping the state of charge of inside cells in the same level, is of great importance to maximize the capacity of whole battery pack and keep cells away from overcharge and overdischarge damage. In this paper, based on the analysis of bi-directional Cuk converter, we have proposed a fuzzy controller to adaptively tune the equalizing current. The inputs of fuzzy controller are selected as the difference in state of charge, the average of state of charge and the total internal resistance. The overall performance of the proposed equalizer is evaluated by multi-indexes such as equalizing speed, efficiency and cell protection. Simulations are conducted based on a well established 6Ah Li-ion battery provided in Advisor. The results under various initial conditions show that the proposed equalizer has the ability to balance the equalizing speed and efficiency. Any pair of cells with difference in state of charge less than 0.3 can be equalized within one hour and with the energy efficiency around 0.95.

Self-adaptive model-based ECG denoising using features extracted by mean shift algorithm

Abstract Denoising of electrocardiogram (ECG) is the fundamental technique for manual or automatic ECG diagnosis. Model-based denoising has attracted initial studies since the ECG dynamical model was established in 2003 and been demonstrated to outperform most model-less denoising methods. The focus of this paper is robust denoising of abnormal ECG signals, which do not satisfy the assumption in previous model-based studies that morphological or physiological variations are small from one beat to another. A mean shift based initializer is proposed to provide a much more robust estimation of initial model parameters for each heart beat. Together with physiological knowledge based wave sub-segmentation and enhanced strategies, the novel initializer has been demonstrated to achieve satisfactory performance for both normal and abnormal heart beats under both white and pink noises. Utilizing records from Massachusetts Institute of Technology (MIT)-Beth Israel Hospital (BIH) database, this paper also applies various filters to denoise noisy signals and the denoising performances verify the availability and efficacy of the proposed denoising method.

Energy management for four-wheel independent driving vehicle

The promising electric vehicle (EV) technology is a direction to tackle the global non-renewable energy problem. However, the efficiency to use the electric energy still needs deliberate research. Traditional EV has no choice to manage its energy flow, because it has only one traction motor. With the robotic research in 4 wheel independent drive (4WID), the driving task of the single traction motor can be shared by 4 independent in-wheel motors. By exploring the motor efficiency map, we propose the energy management strategy based on optimal driving torque distribution (ODTD). The total input power of the 4 motors can be minimized while the driving performance is still maintained, and electric energy consumption can be reduced compared with traditional single motor driving EV. Simulation results validate the proposed strategy. The energy management strategy can also be applied to multi-driving-wheel mobile robots.

Battery state-of-charge estimation based on H ∞ filter for hybrid electric vehicle

State-of-charge (SOC) estimation is the most difficult problem in battery management system, which is one of the key component of electric vehicle and hybrid electric vehicle. Suffered from the non-zero mean noise and uncertain model parameters in practice, the conventional current integral and Kalman filter estimation methods can not achieve the required accuracy, even causing nonconvergent results. The essential difficulties to apply current integral and Kalman filter to solve SOC estimation problem in colored noise and time-variant battery system are analyzed. Hinfin filter, an estimator designed to handle the estimation problem in noised and uncertain situation, is then applied to calculate SOC online. The simulation experiment based on a typical battery model verifies the availability and efficiency of the proposed method.

Battery Fast Charging Strategy Based on Model Predictive Control

Battery fast charging is a crucial issue in both research and application to realize and promote the mass commercialization of electric vehicles, especially pure electric vehicles. However, due to the strong nonlinear properties of batteries, the charging process should take into consideration various factors such as state of charge (SoC), temperature, and charging current, so as to assure the safety, reduce charging time, and enhance charging efficiency. In this paper, we propose a fast charging strategy under the model predictive control framework. Two models are employed to predict SoC and temperature under a sequence of future charging currents. SoC predictor is based on RC equivalent circuit and temperature predictor is based on thermal conduction and convection. The prediction of battery future states allows optimization of the control sequence, with the objectives to follow a predetermined SoC trajectory and to minimize battery temperature rising. Genetic algorithm are introduced to solve the constrained multi-objective optimization problem. The results using Advisor platform demonstrate the availability and efficacy of the proposed framework and prove that it has the ability to reduce charging time and heat generation simultaneously.

A novel on-line self-learning state-of-charge estimation of battery management system for hybrid electric vehicle

State-of-charge (SOC) estimation is the most difficult problem in battery management system, which is one of the key component of electric vehicle and hybrid electric vehicle. Suffered from the non-zero mean noises in practice, the conventional current integral and Kalman filter estimation methods can not achieve the required accuracy, even causing nonconvergent results. According to the SOC truth value obtained by Open-circuit-voltage Vs. SOC curve at each vehicle start time, we deduce a mathematic formula to calculate the mean values of system noises and then a self-learning strategy is proposed to improve the current integral and Kalman filter methods in colored noise environment. The simulation experiment based on a typical battery model verifies the availability and efficiency of proposed strategy.

Performance analysis of routing protocols for vehicle safety communications on the freeway

In a freeway vehicular ad hoc network (VANET) environment, an efficient ad hoc routing protocol plays a very important role to enhance the safety of passengers. This paper presents the latest result of simulation model of three mobile ad hoc routing protocols: destination-sequenced distance-vector protocol (DSDV), dynamic source routing (DSR) and ad hoc on-demand distance vector (AODV). The performance of three protocols under constant bit rate traffic is evaluated and compared with five quality indices. The simulation results show that both the reactive routing protocols, DSR and AODV, have better performance than the proactive routing protocol DSDV. DSDV has largest packet loss rate and smallest system throughput among the three protocols. This paper also shows that the effect of varying mobility has undeniably influenced the performance of both reactive routing protocols. DSR is better in the protocol overhead than AODV. However, there is critical jitter variation in the DSR. As a whole, AODV is more appropriate than DSR for the freeway VANET.

Multi-objective parameters optimization of electric assist control strategy for parallel hybrid electric vehicle

To manage the drivestrain and power flow of hybrid electric vehicle (HEV) and achieve balanced performances on fuel economy, emissions, grade ability and acceleration ability, it is necessary to develop a control system with suitable parameters by solving a multi-objective optimization problem. Based on the proof of the relationship between dominating number and diversity in objective-space, a dominating number based multi-objective genetic algorithm is proposed to enhance the diversity of Pareto-front and has been applied to optimize parameters of electric assist control strategy for parallel HEV under standard test procedure provided in Advisor. Simulations under four drive cycles demonstrate availability and efficacy of the proposed algorithm.

INTELLIGENT DIAGNOSIS OF CARDIOVASCULAR DISEASES UTILIZING ECG SIGNALS

Early automatic detection of cardiovascular diseases is of great importance to provide timely treatment and reduce fatality rate. Although many efforts have been devoted to detecting various arrhythmias, classification of other common cardiovascular diseases still lacks comprehensive and intensive studies. This work aims at developing an automatic diagnosis system for myocardial infarction, valvular heart disease, cardiomyopathy, hypertrophy, and bundle branch block, based on the clinic recordings provided by PTB Database. The proposed diagnosis system consists of the components as baseline wander reduction, beat segmentation, feature extraction, feature reduction and classification. The selected features are the location, amplitude and width of each wave, exactly the parameters of ECG dynamical model. We also propose a mean shift algorithm based method to extract these features. To demonstrate the availability and efficacy of the proposed system, we use a total of 13,564 beats to conduct a large scale ex...

Traction/braking force distribution algorithm for omni-directional all-wheel-independent-drive vehicles

In this paper, a traction/braking force distribution algorithm for omni-directional all-wheel-independent-drive vehicles is proposed as a tool to enhance driving stability. In the proposed algorithm, the amount of the traction or braking force on each driving wheel can be determined so as to generate a desired tangential force, yaw moment and centripetal force independently. The algorithm considers omni-directional steering command and is capable of handling both traction and braking force commands. The algorithm is applicable on vehicles with at least three independent driving wheels. Simulations have been conducted to illustrate the use of the proposed force distribution method in enhancing vehicles stability.