CENS Energy Technology Co.

Hangzhou, China

CENS Energy Technology Co.

Hangzhou, China
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Wang H.,Beijing Institute of Technology | Wang H.,Harbin University of Science and Technology | Wu F.,Beijing Institute of Technology | Wu B.,Beijing Institute of Technology | And 4 more authors.
EVS 2010 - Sustainable Mobility Revolution: 25th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition | Year: 2010

The cost and security of the of LiFePO4 power battery is a critical factor in the application of the electric vehicles. The paper describes a management system use MPC5510 and LF2407 as the core, POWER PC and the DSP as the main body to build the hardware platform of the battery management system. Embed μC/OS-II in POWER PC and DSP respectively as the real-time operating system. And achieve multiple tasks and CAN bus design of the phosphate iron lithium of power battery management system to improve the vehicle system's real-time and stability.


Yu Z.,Northeast Forestry University | Yu Z.,Harbin University of Science and Technology | Guo Y.,Northeast Forestry University | Hao Z.,Harbin University of Science and Technology | Li G.,CENS Energy Technology Co.
ICIC Express Letters, Part B: Applications | Year: 2013

The equivalent circuit of battery on the foundation of electronic movement theory is established, as well as the temperature revision on the model, in order to conduct real-time monitoring of state of charge (SOC) and the relationship between SOC and temperature of battery. Extended Kalman filter (EKF) algorithm is included in the method to conduct prediction on SOC of battery, and the state observer on SOC is established to conduct simulated condition experiment on lithium-iron-phosphate power battery under environment of 20±2°C and -20±2°C. The results have indicated that the observer of dynamic system on battery constructed by the revised model can conduct effective compensation to SOC, and that the max error of SOC under different temperature after revised is 1.36% and 2.7% respectively. © 2013 ISSN 2185-2766.


Ran L.,Harbin University of Science and Technology | Junfeng W.,Harbin University of Science and Technology | Gechen L.,Harbin University of Science and Technology | Gechen L.,CENS Energy Technology Co.
Lecture Notes in Electrical Engineering | Year: 2012

It has a strong request to real-time communication and sharing the information between each subsystem of hybrid electric vehicle (HEV). The mainstream of constructing network of hybrid electric vehicle applies the CAN Bus system. It follows the standard SAE J1939 protocol, uses the characteristics of the motor and inverter. In order to achieving superior braking, the total braking moment is divided into energy regeneration braking, mechanical breaking and ABS breaking, according to the actual situation, which are divided into different proportion. Finally, in the road test on the actual data collection, verification of the hybrid electric vehicle CAN bus control network hardware and software modules designed with the academic value and practical application. © 2012 Springer-Verlag GmbH.


Wang H.,Harbin University of Science and Technology | Liu P.,Harbin University of Science and Technology | Zhao Y.,Harbin University of Science and Technology | Du L.,Harbin University of Science and Technology | Li G.,CENS Energy Technology Co.
International Journal of Control and Automation | Year: 2016

In the actual application process, power battery may not behave properly, such as insufficient charging, internal resistance increment, capacity reduction and etc, the paper establishes a fuzzy comprehensive evaluation model of power battery to diagnose judge and analyze. The diagnostic results are given in the form of battery health status DOH and maintenance information. The paper tests the model through Actual working conditions of electric vehicle, and the results show that the actual fault information is consistent with the diagnostic results of model. The model is reasonable, and it can be used to diagnose the faults of power battery. © 2016 SERSC.


Wang H.,Harbin University of Science and Technology | Fu H.,Harbin University of Science and Technology | Liu Y.,Harbin University of Science and Technology | He Y.,Harbin University of Science and Technology | And 2 more authors.
ICIC Express Letters, Part B: Applications | Year: 2013

The research focus of power battery for electric vehicles should embrace not only its output peak power, but its real-time output power, to achieve perfect characteristics in both power and economy, and to maintain the electric vehicle working within best performance area and to extend battery life as well. This paper probes into the application of two-stage pulse discharging, multi-stage pulse discharging, and constant power discharging method on testing the peak power of Li-ion battery. Conduct analysis on the experimental data obtained from three methods above, using linear function, exponential function, and polynomial function to achieve estimation of continuous discharging on Li-ion peak power output for 10s, and evaluation of the accuracy of the estimated value of three functions, and obtain the minimum error of the exponential prediction function, on the basis of which, prediction model of the power battery power status is established based on BP neural network. The impact on the accuracy of the prediction results of Back Propagation (BP) neural network is being tested in deep after analyzing the discrepancy in the simulation results of trainscg, trainlm and traincgb, three neural network training algorithms. Experimental results have indicated that the model mentioned above has high accuracy, which can meet the error requirements of the prediction. © 2013 ISSN 2185-2766.


Wang H.,Harbin University of Science and Technology | Liu S.,Harbin University of Science and Technology | Sun T.,Harbin University of Science and Technology | Li G.,Harbin University of Science and Technology | Li G.,CENS Energy Technology Co.
International Journal of Smart Home | Year: 2013

In dealing with the increment in environment pollution and source consumption, research has focused on the application of renewable energy source. Batteries, especially power batteries, which has great prospects in the fields, are among the attention. Rechargeable batteries are widely used in many electrical systems to store and deliver energy. However, there is a wide variety of Power Batteries and they have different weak Points. In order to develop and apply battery in a more efficient and appropriate method, their response to various operating conditions must be understood. Knowing the battery temperature variation in electric vehicles (EVs) is very important issue. Temperature depends on ambient temperature, charging current and charging time. Recently neural networks have been successful used for power system applications. In the literature, there are many neural networks for power system applications. However, Back Propagation (BP) has demonstrated better capabilities. This paper presents neural network for temperature estimation of power batteries. The main contribution of this paper is consideration of non-uniform temperature field and the temperature effect in batteries. In addition, the results of estimation and actual measured values are compared, proving the feasibility and accuracy of the method.


Wang H.,Harbin University of Science and Technology | Liu Y.,Harbin University of Science and Technology | Fu H.,Harbin University of Science and Technology | Li G.,Harbin University of Science and Technology | Li G.,CENS Energy Technology Co.
International Journal of Control and Automation | Year: 2013

State of charge (SOC) can be applied in various fields characterized as an important parameter for estimating residual capacity state of battery. It is obtained from current or collected data, such as voltage, current and temperature as well. The accuracy of estimation of SOC of power battery can be essential and premise in designing the battery management system. Researchers in the fields shall take it an important and challenging task, requiring lots of work and energy, in order to improve the accuracy in estimation of SOC for eletric vehicles (EV). The SOC estimation tasks have made it great headway from classical and typical methods. This paper has proposed the shortcomings over various existed estimation methods and discussed the definition of SOC in details in the application. Study on the principle and application of the SOC estimation algorithm against many existing technical difficulties of SOC estimation algorithm for power batteries is very necessary. This paper analyzes the influence of charge and discharge rate, temperature, self-discharge and aging on SOC. It has important meaning for the further development of power battery SOC estimation.


Wang H.,Harbin University of Science and Technology | He L.,Harbin University of Science and Technology | Qi X.,Harbin University of Science and Technology | Li G.,CENS Energy Technology Co. | Dai X.,CENS Energy Technology Co.
Proceedings of 2012 International Conference on Measurement, Information and Control, MIC 2012 | Year: 2012

Aiming at the uncertain problem of dynamic performance evaluation of power battery for electrical vehicle, this paper researched deep on the establishment of simulation system of the performance of Li-on power battery for electrical vehicle in different working conditions by comparing and analyzing the general structure of simulation system of the performance of electrical vehicle in and abroad combined with the characteristic of pure electrical vehicle, and proposed an on-line performance simulation method of Li-on power battery for electrical vehicle based on the technology of Internet of things. Design for data acquisition, hardware simulation of charging and discharging of the simulation system and the running state monitoring for simulation platform are also included in this paper. It is of most importance for the development of electrical vehicle and Li-on power battery system for electrical vehicle of our country. © 2012 IEEE.


Li R.,Harbin University of Science and Technology | Wu J.-F.,Harbin University of Science and Technology | Wang H.-Y.,Harbin University of Science and Technology | Guo J.-Y.,Harbin University of Science and Technology | And 2 more authors.
Information Sciences | Year: 2014

In this paper, we present experimental data on the resistance, capacity, and life cycle of lithium iron phosphate batteries collected by conducting full life cycle testing on one type of lithium iron phosphate battery, and we analyse that data using the data mining method of pattern recognition. We also predict battery reliability using cluster analysis. A strategy for enhancing the reliability of lithium iron phosphate batteries is proposed based on a statistical analysis and study of the macromechanism of product failures. We show in practice that the average life cycle of a battery is increased by 45.5% after adopting a new strategy that we suggest. The strategy is effective for mass-producing reliable lithium iron phosphate batteries and instructive for improving the industry of lithium iron phosphate battery production, as well as the quality of its products. © 2013 Elsevier Inc. All rights reserved.


Patent
CENS Energy Technology Co. | Date: 2010-03-31

The invention discloses a battery connection device, which includes a connection block that, made of insulating material, is positioned at an electrode end of a battery; the connection block is provided at both ends with a series connection mechanism, respectively, and at all sides with a parallel connection mechanism, respectively; the series connection mechanism is provided inside with a conductive slice electrically connected with the electrode end of the battery; the conductive slice is further led out to a fitting face of the parallel connection mechanism; and thus the conductive slices on the two connection blocks are electrically connected when the two batteries are parallel which are respectively provided with the connection block. The invention can make each unit battery connected modularly in series or parallel like a building block; the battery set obtained from this connection does not further need electrode connection by welding or battery fixing by assembling, which is convenient for operation as well as safe and reliable.

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