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rdf:type
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Description
| - *The current report delivers determination of current vehicle parameters (deliverable D 3.4), namely variable payload and driving resistances. The change of them during driving may be important for the up-dated range estimation, which is enabled by Predictive and Adaptive Control Algorithms (PACA). Two independent methods for highly variable payload of a commercial vehicle have been developed, using two-axes accelerometers. Longitudinal (roll axis) acceleration/deceleration is used for both payload (driver&cargo load) and rolling resistance determination. Additionally, eigen frequency in yaw axis direction yields information on payload, as well. Cargo and crew mass determination seems to be feasible using standard signals. The procedure using acceleration-deceleration seems to be robust considering independency on rolling resistance but demanding considering accelerometer accuracy. Rolling and other resistances, on the other side, are dependent on the knowledge of the current slope of road. They may be checked and – at least – calibrated from integral daily results. The appropriate input of tire parameters after changing them (summer – winter, low friction types, etc.) should be treated in the system data input. Information on altitude and – if possible - vehicle longitudinal axis position (road slope) by direct measurement in a quiet state (without any acceleration) or at least slope information from a route map should be added to the log list. The total mass errors are a significant source in range prediction. The highest care should be devoted to it, otherwise the range predictions may be rather unreliable. Data redundancy may be used for false result avoidance, combining both proposed dynamic methods based on accelerometers in a vehicle and motor torque diagnostics. Information on altitude and – if possible - vehicle longitudinal axis position (road slope) by direct measurement in a quiet state (without any acceleration) or at l
- *The current report delivers determination of current vehicle parameters (deliverable D 3.4), namely variable payload and driving resistances. The change of them during driving may be important for the up-dated range estimation, which is enabled by Predictive and Adaptive Control Algorithms (PACA). Two independent methods for highly variable payload of a commercial vehicle have been developed, using two-axes accelerometers. Longitudinal (roll axis) acceleration/deceleration is used for both payload (driver&cargo load) and rolling resistance determination. Additionally, eigen frequency in yaw axis direction yields information on payload, as well. Cargo and crew mass determination seems to be feasible using standard signals. The procedure using acceleration-deceleration seems to be robust considering independency on rolling resistance but demanding considering accelerometer accuracy. Rolling and other resistances, on the other side, are dependent on the knowledge of the current slope of road. They may be checked and – at least – calibrated from integral daily results. The appropriate input of tire parameters after changing them (summer – winter, low friction types, etc.) should be treated in the system data input. Information on altitude and – if possible - vehicle longitudinal axis position (road slope) by direct measurement in a quiet state (without any acceleration) or at least slope information from a route map should be added to the log list. The total mass errors are a significant source in range prediction. The highest care should be devoted to it, otherwise the range predictions may be rather unreliable. Data redundancy may be used for false result avoidance, combining both proposed dynamic methods based on accelerometers in a vehicle and motor torque diagnostics. Information on altitude and – if possible - vehicle longitudinal axis position (road slope) by direct measurement in a quiet state (without any acceleration) or at l (en)
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Title
| - *D3.4 Procedures for determination of the current vehicle parameters
- *D3.4 Procedures for determination of the current vehicle parameters (en)
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skos:prefLabel
| - *D3.4 Procedures for determination of the current vehicle parameters
- *D3.4 Procedures for determination of the current vehicle parameters (en)
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skos:notation
| - RIV/68407700:21220/14:00229297!RIV15-MSM-21220___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/68407700:21220/14:00229297
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - Measurement; operating conditions; identification (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...telVyzkumneZpravy
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Macek, Jan
- Steinbauer, Pavel
- Barák, Adam
- Morkus, Josef
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number of pages
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http://localhost/t...ganizacniJednotka
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