scholarly journals Design of Control Area Network Protocol

2012 ◽  
Vol 591-593 ◽  
pp. 1579-1584
Author(s):  
Jyh Wei Chen ◽  
Huan Fu Lin

A grid-connected parallel inverter with interleaved phase shift is proposed in this paper. The synchronous are generated by the master module to achieve interleaving phase shift PWM for the parallel inverters connected to grid-tied system that make the inverter to output current to the power line and share the load. TI TMS320F2812 DSP is used for system feedback control with voltage and current by using A/D converters to generate the output current close to sine wave. The expected output current values are determined by the master module and transmitted via CAN (Control area network) between inverter modules. The grid-tied system uses zero-voltage-detection circuit to synchronize the inverter currents with grid voltage. For each switching period, PWM voltage of two inverters are interleaved to reduce the total output current ripple so that the switching frequency can be reduced and the power system EMI problem can be alleviated as well. The experiment results are provided to verify the performance of the proposed system to reduce output current harmonic distortion.


2018 ◽  
Vol 8 (9) ◽  
pp. 1594 ◽  
Author(s):  
YiNa Jeong ◽  
SuRak Son ◽  
EunHee Jeong ◽  
ByungKwan Lee

This paper proposes a Lightweight In-Vehicle Edge Gateway (LI-VEG) for the self-diagnosis of an autonomous vehicle, which supports a rapid and accurate communication between in-vehicle sensors and a self-diagnosis module and between in-vehicle protocols. A paper on the self-diagnosis module has been published previously, thus this paper only covers the LI-VEG, not the self-diagnosis. The LI-VEG consists of an In-Vehicle Sending and Receiving Layer (InV-SRL), an InV-Management Layer (InV-ML) and an InV-Data Translator Layer (InV-DTL). First, the InV-SRL receives the messages from FlexRay, Control Area Network (CAN), Media Oriented Systems Transport (MOST), and Ethernet and transfers the received messages to the InV-ML. Second, the InV-ML manages the message transmission and reception of FlexRay, CAN, MOST, and Ethernet and an Address Mapping Table. Third, the InV-DTL decomposes the message of FlexRay, CAN, MOST, and Ethernet and recomposes the decomposed messages to the frame suitable for a destination protocol. The performance analysis of the LI-VEG shows that the transmission delay time about message translation and transmission is reduced by an average of 10.83% and the transmission delay time caused by traffic overhead is improved by an average of 0.95%. Therefore, the LI-VEG has higher compatibility and is more cost effective because it applies a software gateway to the OBD, compared to a hardware gateway. In addition, it can reduce the transmission error and overhead caused by message decomposition because of a lightweight message header.


Author(s):  
M. McIntyre ◽  
A. Vahidi ◽  
D. Dawson

This work proposes a two stage estimation strategy to determine a heavy duty vehicles's mass and road grade. The estimation strategy uses standard signals available through the vehicle control area network. The first stage of this approach utilizes an adaptive least-squares estimation strategy to determine the vehicle's mass. Due to the time varying nature of the road grade, a nonlinear estimator is then developed that provides a more accurate estimate of the road grade. An estimation analysis is provided for both stages that proves, under a set of qualifying conditions, both the mass and road grade can be estimated. The validity of this two stage approach is verified using experimental data.


Author(s):  
Soheil Mohagehghi Fard ◽  
Amir Khajepour

The goal of this paper is to estimate the mass and auxiliary power of a vehicle simultaneously. Auxiliary power is the portion of the load power that is consumed by any auxiliary devices such as A/C compressor which is connected to the engine directly. This estimation has many potential applications especially in power management control systems of hybrid and plug-in-hybrid vehicles to improve their efficiency. The parameter estimation algorithm is based on power balance of the vehicle. That is, total generated power by the engine should be equal to the power required for moving the vehicle plus the power consumed by the auxiliary devices. After developing the system model, Kalman filter is applied for the estimation of the auxiliary power and vehicle mass. The proposed estimation algorithm uses the signals available through the vehicle control area network (CAN), and no extra sensor is required. It is assumed that the road grade is provided by a Global Positioning System (GPS) installed in the car. Simulations are presented to show the performance of the estimation algorithm in both city and highway driving cycles. The estimated and actual results are in very good agreement.


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