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The ringing and the resulting asymmetry in the propagation delay are the main causes of bandwidth degradation and communication errors in a controller area network (CAN) with flexible data rate. Therefore, in this paper, the mechanism of ringing is analyzed, and the ringing suppression circuit is proposed based on the analysis. The proposed circuit includes an impedance matching resistor and a forward-biased diode for terminating the repetition of reflections and limiting the magnitude of the ringing. These components are temporarily connected by operating a switch that is controlled by the TxD signal of a CAN controller so that the ringing suppression circuit only engages when necessary and at the correct time. The performance of the ringing suppression circuit is verified by experiments. The experimental results show that the proposed circuit keeps the ringing adequately suppressed and the good symmetry in the propagation delay across the physical bus is possessed.

Signal distortion, called ringing, in a controller area network with flexible data rate (CAN-FD) causes asymmetry in propagation delay throughout a network, which is dependent on its physical bus design and becomes a critical issue in limiting the data rate. Thus, in this paper, the bus structure of a CAN-FD is investigated and a transfer function of ringing is modeled by considering the physical bus configuration and features of a controller area network transceiver. The effects of the main parameters of the physical bus, such as the stub line length and number of stub lines connected to a joint connector, are then quantitatively analyzed using the presented model. When a practical bus structure is considered, additional signal distortion owing to a neighboring connector in a physical bus is modeled and analyzed. These analytical results are confirmed experimentally. Their comparison shows that the presented model-based analysis can closely approximate the size and time response of ringing and the extent of bit time distortion. The presented model-based analysis facilitates reliable communication performance by estimating the ringing and resulting asymmetry of the propagation delay for a given physical bus design and, if necessary, adjusting the design.

This paper proposes a distance-based two-stage energy management strategy for power-split plug-in hybrid electric vehicles (PHEVs). One stage is for long-term optimization and the other is for short-term adaptation to actual traffic conditions. Energy consumption in PHEVs depends on the characteristics of the drivetrain as well as the operating conditions such as power demands and their split. Thus, prior to departure, the operating conditions for a whole trip are optimized for the drivetrain characteristics and trip information, which generates optimal speed and state-of-charge profiles. While driving, the operating conditions are adapted to current traffic conditions for a short horizon on the basis of long-term optimization results. In consideration of the changeability of traffic conditions, the proposed energy management strategy is performed in a distance domain, which localizes the effects of changes in traffic conditions on the long-term optimization results. Therefore, this distance-based two-stage strategy improves the balance between the optimality and the real-time computing time, which is suitable for online management. A model for the propulsion system in a PHEV and the energy management strategy were formulated in a distance domain. An estimation of distribution algorithm was used for long-term optimization and local adaptation.

This paper proposes a distance-based two-stage ecological (eco-) driving scheme by using estimation of distribution algorithms (EDA) and model-based prediction of traffic conditions. Before departure, the optimal speed profile for an entire route is generated by an EDA in combination with speedup approaches for a faster computing time, which can optimize the complex cost function of ecodriving without simplification within a reasonably short computing time. This optimization is performed in a distance domain for localizing changes in the optimal speed profile due to traffic conditions while driving. After departure, by taking the optimal speed profile and actual traffic conditions into consideration, the speed profile for a short term—to only the next location—is adapted. In order to reliably react to actual traffic conditions, additional points are interpolated into the long-term distance step and fine control of speeds at the additional points is established, which is based on a predictive model for estimating the spacing to the preceding vehicle. The proposed ecodriving system is evaluated in two types of route conditions, and its results are compared with the optimization result by the quadratic programming method. This comparison shows that an EDA can generate a speed profile with better optimization results in terms of fuel efficiency and driving time within a shorter computing time.

This paper proposes a distance-based ecological (eco)-driving scheme with two stages: one for long-term speed optimization and the other for short-term adaptation to actual traffic conditions. Before departure, the speed profile for an entire route is optimized in a distance domain by using characteristics of the drivetrain and road conditions. Then, while driving, the speed at only the next location is controlled to follow the optimal speed profile and adapt it for traffic conditions, which allows for real-time adaptation, maintaining optimal driving in the long term. To localize the change of the optimal speed profile due to traffic conditions, models for fuel rate of a conventional vehicle and vehicle propulsion systems were formulated in a distance domain, and a distance-based optimal speed profile was generated. The proposed eco-driving scheme is optimized by the quadratic programming method, and its validity is tested by simulation.