Implementation of discharging/charging current sensorless state-of-charge estimator reflecting cell-to-cell variations in lithium-ion series battery packs

This paper offers novel insights to the design and implementation of an innovative state-of-charge (SOC) estimator for the lithium-ion (Li-Ion) series battery pack. The most interesting feature of this approach is that it can utilize information from each filtered terminal voltage of the Li-Ion cells connected in series for SOC estimation of the battery pack. Without actual sensing each discharging/charging current (DCC) applied to the Li-Ion cells, it is possible to extract each DCC estimation from the corresponding filtered terminal voltages with an equivalent electrical circuit model (EECM) identification of all Li-Ion cells in the battery pack. There are two advantages to SOC estimation of the battery pack with this approach. First, the proposal can be implemented simply and effectively, reducing the computational steps required for SOC estimation. By reducing computational steps, the proposal is expected to be more cost-effective. Second, the approach guarantees an improved SOC performance, even if the battery pack results in inevitable cell-to-cell variation among Li-Ion cells. Accordingly, there are fewer differences to previously estimated DCCs among Li-Ion cells. Specifically, all values from the estimated DCCs are properly compensated for by simultaneous parameter modification according to each cell’s electrochemical characteristics. Experimental results clearly demonstrate that our DCC sensorless SOC estimator provides robust SOC performance for the battery pack. This approach considered an experimental battery pack (12S1P) connected in series using 2.6 Ah LiCoO2 cells produced by Samsung SDI.     

Experimental study on a model azimuthing podded propulsor in ice

The objective of this study was to investigate the performance of a model azimuthing podded propulsor in ice-covered water. Model tests were carried out with two different depths of cut into the ice (15 and 35 mm), two different ice conditions (presawn and pack ice conditions), and four different azimuthing angles. The depth of cut is the maximum penetration depth of the propeller blade into the ice block. The 0.3-m-diameter model propeller was operated in a continuous ice milling condition. Ice loads were measured by several sensors which were installed in various positions on the model. Six one-axis pancake-style load cells on the top of the model measured the global loads and two six-component dynamometers were installed on the shaft to measure the shaft loads. One six-component dynamometer was attached to the one of the propeller blades inside the hub to measure the blade loads. The pod unit and propeller performance in ice are presented. Ice-related loads, which were obtained when the blade was inside the ice block, are introduced and discussed. During the propeller–ice interaction, a blade can experience the path generated by the previous blade, which is called the shadowing effect. The effects of shadowing, depth of cut, azimuthing angle, and advance coefficient on propulsor performance are presented and discussed.     

Strong bottom–up effects on phytoplankton community caused by a rainfall during spring and summer in Sagami Bay,Japan

To assess the consequences of bottom-up effects on phytoplankton community composition during the rainy season, phytoplankton levels and environmental factors were monitored daily from 12 April to 22 July 2003 in Sagami Bay, Japan. The relevant environmental factors were analyzed using cross-correlation analyses. Based on time-series analysis, low surface salinity conditions lasting 0 or 2 days after heavy rainfalls resulted in significant nutrient loading, such as dissolved inorganic nitrogen (DIN), into the coastal area. Also, Chlorophyll-a (Chl-a) concentration frequently increased 2 and 6 days after rainfall. Based on the high total Chl-a concentration, the time was divided into three periods, from 1 to 11 May (Period A), 26 May to 9 June (Period B) and 30 June to 22 July (Period C). The phytoplankton assemblages during Period A were dominated by two dinoflagellates, Ceratium furca and Ceratium fusus. Prior to these species blooming, the heterotrophic dinoflagellate Noctiluca scintillans was dominant. During Period B, the phytoplankton communities were dominated primarily by the diatoms Rhizosolenia delicatula, Hemiaulus sinensis and Navicula spp. Finally, Cerataulina dentata, Rhizosolenia spp., Lauderia borealis and Neodelphineis pelagica were dominant during Period C. After increases in phytoplankton abundance, available nitrogen (N) and phosphorous (P) were consumed and exhausted, which were considered a potential cause of the shift in the dominant organisms from large diatoms to pico- and nano-plankton in the low Chl-a environment. In particular, silicate (Si) was not a major limiting factor for phytoplankton production, since the Si:DIN and Si:P ratios clearly demonstrated that there were no any potential stoichiometric Si limitations, and almost all silicate concentrations were > 2.0 µM during this study. Our results reveal that nutrient sources supplied by river discharge are a main cue for strong bottom–up effects on algal bloom succession during the early summer season in Sagami Bay.     

Assessing the performance of SpeedInfo radar traffic sensors

Traffic speed is a crucial input for real-time traffic management applications. Operating agencies typically deploy their own sensors to collect the measurements, e.g., loop detectors. Recently, SpeedInfo emerged with a different paradigm for traffic speed collection: instead of selling hardware to operating agencies, at each link the company deploys its own Doppler radar in a self-contained wireless unit to measure traffic speeds and then sells the speed data. This study uses well-tuned loop detector-based speed measurements to evaluate 15 of the Doppler radar sensors over several months while the two traffic data collection systems were operating concurrently. The extended study period includes potentially challenging and transient conditions for the radar sensors: both recurrent (rush hour congestion and late night low flow) and nonrecurrent (incidents and precipitation). The analysis took a broad overview, comparing speed measurements from the radar sensors against the concurrent loop detector data and then explicitly looked for any anomalous pattern in the radar data such as latency and system outages. The work found the radar measurements are generally good, but also identified several points that should be considered before deployment, including latency, different biases in free flow and congestion, vulnerability to precipitation, and sensitivity to mounting angle.     

Development of a low-noise cooling fan for an alternator using numerical and doe methods

An alternator, which converts mechanical rotational energy into electrical energy, is an important component of a vehicle. Alternators operate over a broad range of rotational speeds, typically from 3,000 RPM to 18,000 RPM, which demands a cooling fan producing sufficient airflow, ideally with a minimum of noise. In the current study, an optimized alternator-cooling fan was developed through a linked DOE(Design OF Experiment) process and numerical analysis. The SC/Tetra and FlowNoise S/W programs were used to calculate flow rates and noise levels, respectively, for the newly developed fan. Compared with original model, the numerical results predicted a 3 dBA noise reduction; the measured reduction was 4 dBA.     

Development of a navigation algorithm with dead reckoning for unmanned ground vehicles

A navigation algorithm is indispensable for Unmanned Ground Vehicles (UGVs). During driving, UGVs follow a global path. In this study, we propose a navigation algorithm using Real Time Kinematic (RTK)-Differential Global Positioning System (DGPS) units and encoders to complement global path planning. Sometimes GPS systems lose their signals and receive inaccurate position data due to many factors, such as edifice and barrier obstructions. This paper shows that GPS deviations can be solved using a Dead Reckoning (DR) navigation method with encoders and that position errors can be decreased through the use of RTK-DGPS units. In addition to this method, we will introduce a new waypoint update algorithm and a steering algorithm using RTK-DGPS units.     

Modified lateral control of an autonomous vehicle by look-ahead and look-down sensing

This paper presents a modified lateral control method for an autonomous vehicle with both look-ahead and look-down sensing systems. To cope with sensor noise and modeling uncertainty in the lateral control of the vehicle, a modified LMI-based H lateral controller was proposed, which uses the look-ahead information of the lateral offset error measured at the front of vehicle and the look-down information of the vehicle yaw angle error between the reference lane and the centerline of the vehicle. To verify the safety and the performance of the lateral control, a scaled-down vehicle was developed, and the positioning of the vehicle was estimated with USAT. The proposed controller, which uses both look-ahead and look-down information, was tested for lane changing and reference lane tracking with both simulation and experiment. The simulation and experimental results show that the proposed controller has better tracking and handling performance compared with a controller that uses only the look-ahead information of the target heading angle error.     

Piston-temperature measuring system using electromagnetic induction with verification by a telemetry system

The development of an inner-piston-chamber temperature measurement system is a necessary step in engine development or when solving other fundamental problems related to automotive engines. There are various pre-existing measurement methods available, e.g., the linkage method, piston telemetry, templog, and the electromagnetic induction method. In this study, we first redesigned the coil sensor used in the electromagnetic induction method using PEEK and then used Taguchi methods to reduce the number of experiments in the development process and finally utilized piston telemetry via Bluetooth to verify the precision and accuracy of the redesigned PEEK coil sensor and electromagnetic induction method. The results displayed a reproducibility within 0.5 degrees and an accuracy within 2 degrees Celsius.     

Engine performance and toxic gas analysis of biobutanol-blended gasoline as a vehicle fuel

A comprehensive study evaluating the performance of biobutanol-blended gasoline in passenger cars was conducted because biobutanol is considered a better biofuel than bioethanol as it has no water solubility and it has a higher caloric value, giving it a higher energy value. Several kinds of samples—suboctane gasoline, 8 volume percentage and 16 volume percentage biobutanol—blended gasoline, and a 10 volume percentage MTBE-blended market sample (as the oxygencontaining gasoline)-were tested to evaluate the engine performance in terms of the detergency of the intake valves and combustion chambers, power, emissions, and fuel efficiency. Additionally, the toxicity of the emissions from these biobutanolblended samples was tested in order to assess the viability of biobutanol as one of the competitive potential substitutes for MTBE as an oxygenator in the near future. The results show that biobutanol-blended gasoline samples had relatively better detergency, relatively higher power, and similar levels of emissions compared with those of MTBE-blended gasoline. Formaldehyde was emitted from all of the samples at almost the same levels and within the error range, whereas biobutanolblended gasoline samples emitted approximately three times the amount of acetaldehyde than did the suboctane gasoline. This study shows that biobutanol is one of the best alternative bioalcohol fuels for use in the near future.