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For the electric vehicle motor controller driver section requirements of the multiple isolated power supply problems, analyzed the common DC/DC converter, the single-ended flyback converter was selected as the motor controller auxiliary power supply. Taking into account the parasitic parameters of the high frequency transformer and switch transistor effects on the circuit, the loss model was showed. Its feasibility is verified by experiments. Experimental results showed that the designed RCD clamp circuit switch could effectively reduce stress and meet the requirements of the motor controller.

As the electric vehicles usually run under complex conditions of city road, there always exists parameter perturbation of motor, which will affect the vehicle performance. To solve the problem, an improved sliding mode variable structure control (SMC) method which combines continuous function and reaching law has been proposed in this paper. Then the improved vector control algorithm’s codes are generated automatically in the MMC (Model-based Motor Control) platform. The results show that the improved SMC algorithm has small chattering and strong robustness to the parameter perturbation and the external disturbances.

In the foundation of the realization of sensorless control of permanent magnet synchronous motor(PMSM) based on the traditional sliding mode observer, the paper focuses on the research on the chattering impacts on the estimation of rotor position and speed, which are caused by the sliding mode variable structure control. To weaken the chattering, the paper proposes two kinds of methods. First, the paper designs the saturation function with boundary layer thickness variable instead of sign function in the traditional sliding mode observer. Meanwhile, let the phase-locked loop (PLL) combine to the sliding mode observer, and construct the rotor position signal detection unit. Finally, the paper verifies the correctness and effectiveness of the proposed methods through the theoretical analysis and simulation.

The Infineon AUDO FUTURE series micro-controller is widely applied in automobile power system, to solve the online programming problem, paper designed online upgrade system for Infineon AUDO FUTURE series MCU based on CAN Bus, which uses IAP technique to realize triggering bootloader without adding any hardware. Since all ECUs in vehicle are connected to CAN Bus which use ISO15765 protocol to communicate with each other, the entire download process paper designed follow the ISO15765 protocol. This system is suitable for any chip of this series and paper test it based on TC1767. The experimental result shows that this system has strong reliability with high efficiency.

Accurately identifying road condition can send relevant information to the motor control system, so that control system of the motor can adjust the control strategy timely, eventually, the intelligent and optimal control of electric vehicles is realized. In this paper, according to these mathematical model, the permanent magnet synchronous motors simulation model and vehicles simulation model are proposed. Then, output torque of motor and speed of motor are served as the input of RBF neural network, which helps road condition to be identified. The simulation result shows that the road condition is well identified by proposed method based on RBF neural network.

For the driver in the process of moving inconvenient to manually operated vehicle electronics, as well as the monopoly of foreign technology and other issues related , a framework based on DSP + MCU car speech recognition and control systems is designed. According to the embedded application environment, the corresponding recognition algorithm and the hardware architecture of DSP + MCU are chosen, in which DSP is mainly responsible for voice signal processing work, MCU is responsible for communicating with DSP and MCU to obtain recognition results after speech signal processing, as the final control instructions .The experimental results show that the hardware platform can run normally, and control the car body light on experimental bench.

To solve the problem of updating the software for Vehicle Fault Diagnose Instrument frequently, paper proposed an approach to realize the technology of parsing and matching vehicle diagnostic information based on XML database. Paper discussed the theory and process of the approach and used it to develop the Vehicle Diagnose Instrument based on Android OS. The testing result shows that this approach could be easily realized and improved the efficiency of updating the vehicle information.

Regarding to the electric vehicle (EV) with dual-energy storage system (DESS) composed of batteries and ultra-capacitors, study on the structure and drive modes of DESS, after a detailed analysis of energy storage system based on power, resistance and constraints in driving, establish a mathematical model of energy management system of EV with DESS, and an energy management based on the fuzzy control strategy is designed. Finally, a simulation of EV with DESS by using ADVISOR simulation platform is studied, whose results show that the EV with DESS based on fuzzy control strategy can be more effective in distributing power between energy storage systems, and the dynamic performance as well as economic efficiency are also improved

In this paper, the test bench for electric vehicle drive system is designed and the real-time display of speed, torque, current, voltage and other conventional parameters are realized that can offer lots of authentic data for motor performance evaluation, motor parametric design and optimizing control strategy. Road simulation is an important function in the test bench, so the paper analyses the driving electric vehicle in the longitudinal and gives the theoretical dynamometer dynamic output load values that can provide the theory reference for the further implementation of road conditions simulation based on LabVIEW. Finally, in order to validate the test bench feasibility, the start, accelerated and deceleration tests are implemented and show good performance of the bench.

One method which is based on model to settle the long development cycle of driver motor control software is adopted for Electric Vehicle (EV). It is to achieve Field Oriented Control algorithm (FOC) designing, model building, and microcontroller driver integration, task scheduling, code generation; Model simulation experiments are completed aiming at three kinds of running conditions such as a constant speed, accelerating, on load; finally, these running conditions are realized in EV and dynamometer platform. Simulation and experimental results show FOC has a well performance on speed regulating by comparing technical parameters with Chang An Ben Ben Mini, adopting the method also shorten the development cycle of motor control software.

In the present study, we observed the expression of toll-like receptor 4 (TLR4) and its downstream signal pathway in peripheral blood monocytes (PBMs) from patients with acute cerebral infarct (ACI). The expression of TLR4 and MyD88 by PBMs was determined by flow cytometry and reverse transcriptase-polymerase chain reaction, and nuclear factor-κB (NF-κB) activity was detected by electrophoretic mobility shift assay. Ischemia/reperfusion injury-induced cerebral edema, infarction area, and neurologic impairment scores were determined in MyD88 gene knockout mice. The results indicated a significant increase in circulating TLR4+ monocytes in ACI patients as compared with the control group and the transient ischemia attack (TIA) group. This change paralleled an elevation in TLR4mRNA transcription and serum tumor necrosis factor-α (TNF-α) and interleukin (IL)-6 in the ACI and TIA groups. Correlation analysis showed TLR4 expression to significantly correlate with cytokine levels and stroke severity. MyD88mRNA differed insignificantly among the three groups. Compared with wild-type mice, 6 h of cerebral ischemia followed by 24 h of reperfusion did not significantly change cerebral edema, cerebral infarction area, and neurologic impairment scores in MyD88 gene knockout mice. Compared with the control group, serum heat shock protein (HSP) 60 increased significantly in the ACI and TIA groups, leading to NF-κB activation in TLR4/CD14-transfected HEK293 cells. It is suggested that upregulated TLR4 expression on PMBs may act as one of the peripheral mechanisms of inflammatory injury after ACI. Moreover, circulating HSP60 may be a ligand for TLR4, which is involved in the peripheral mechanism of inflammatory injury after ACI, possibly through an MyD88-independent signal pathway.

A battery management system (BMS) based on the LIN-Bus was designed for the Valve Regulated Lead Acid Battery (VRLA). The VRLA BMS plays an important role as a vehicle power supply system which is part of the entire vehicle system. In order to improve the stability of various sub-systems inside the vehicle, VRLA parameters estimation, including current, voltage and temperature, are very important. However, due to lead-acid battery charging and discharging are a complex process of the electrochemical process. The VRLA BMS is consisted of a VRLA battery, a NI USB-8476 LIN transceiver manufactured by National Instruments(NI), a battery test system(BTS) and a high stability, high reliability ADuC7033 for which is high precision and rapid data acquisition ARM7 chip. The hardware design of sampling circuit, the whole VRLA BMS system structure, the software design of keil ARM7 and LabVIEW8.5 and LIN Bus communication were introduced for realtime on-line monitoring and controlling. Experimental results show that measurement is high credible and the error is within 1%. The BMS that was proposed by this paper can be used in Electric Vehicle(EV).

Chang-Hao Piao1,2,3, Wen-Li Fu1,3, Jin-Wang3, Zhi-Yu Huang1,3 and Chongdu Cho4 1Chongqing University of Posts and Telecommunications (Key Laboratory of Network Control & Intelligent Instrument), 2Chongqing Changan New Energy Automobile CO, LTD, 3Chongqing University of Posts and Telecommunications(Research Institution of Pattern Recognition and Application), 4INHA University of Korea (Department of mechanical Engineering) 1,2,3China 4Korea

To track the state of charge (SOC) of Ni-MH battery pack at the hybrid electric vehicle, an artificial neural network (ANN) is designed. Current, voltage and the previous SOC are used to inputs of ANN, and output is SOC. The result show that, this artificial neural network can track the state of charge(SOC) of the batteries accurately, in the average tracking error less than 5%; the ANN is in low dependence on the initial SOC, and the output can be achieved target value only in 90 seconds.