24 research outputs found
Valovitost momenta vrtnje direktnog pogona
Pogonski mehanizmi s direktnim pogonima postaju sve interesantniji svojom rasprostranjenoÅ”Äu i zauzimaju sve znaÄajniju primjenu u tehniÄkim sustavima. Å uplja izvedba pogonskog Älana, kratke aksijalne duljine predstavlja pogodnu strukturu koja se može integrirati u male prostore ugradnje. Kratka vremena pri pokretanju i zaustavljanju uz preoptereÄenost momentom vrtnje daju ovakvim pogonima moguÄnost vrlo brzih odziva u radu. ToÄnost kutnog pozicioniranja je svakako znaÄajka koja proizlazi iz davaÄa pozicije, dok ponovljivost iskljuÄivo ovisi o toÄnosti cjelokupne izrade elemenata direktnog pogona. Pored navedenih nedostataka (visoka cijena, prisilno hlaÄenje vodom) valovitost razvijenog momenta vrtnje može pogorÅ”ati performanse u zahtjevnim pogonima. Pri radu u praznom hodu glavnog pogona, amplitude valovitosti momenta vrtnje uslijed debalansa rotora su zanemarive, dok su amplitude valovitosti momenta zbog promjenjive magnetske reluktancije momenta vrtnje motora unutar oÄekivanih vrijednosti
Damping Optimum-Based Design of Control Strategy Suitable for Battery/Ultracapacitor Electric Vehicles
This contribution outlines the design of electric vehicle direct-current (DC) bus control system supplied by a battery/ultracapacitor hybrid energy storage system, and its coordination with the fully electrified vehicle driveline control system. The control strategy features an upper-level DC bus voltage feedback controller and a direct load compensator for stiff tracking of variable (speed-dependent) voltage target. The inner control level, comprising dedicated battery and ultracapacitor current controllers, is commanded by an intermediate-level control scheme which dynamically distributes the upper-level current command between the ultracapacitor and the battery energy storage systems. The feedback control system is designed and analytical expressions for feedback controller parameters are obtained by using the damping optimum criterion. The proposed methodology is verified by means of simulations and experimentally for different realistic operating regimes, including electric vehicle DC bus load step change, hybrid energy storage system charging/discharging, and electric vehicle driveline subject to New European Driving Cycle (NEDC), Urban Driving Dynamometer Schedule (UDDS), New York Certification Cycle (NYCC) and California Unified Cycle (LA92), as well as for abrupt acceleration/deceleration regimes
Procjena stanja dinamike vozila zasnovana na fuziji senzora primjenom adaptivnoga Kalmanova filtra
An increasing number of vehicle dynamics control systems are being embedded into modern vehicles in order to assure safety and comfort of driving. All of these systems require information on the vehicle dynamics state variables (e.g. yaw rate, sideslip angle, roll rate etc.). Some of them can be measured, while others need to be estimated based on available measurements and appropriate vehicle kinematics/dynamics models. This thesis presents a contribution to the research of yaw rate and sideslip angle estimation. More specifically, a kinematic sensor fusion-based yaw rate estimator has been proposed, which combines the wheel speeds measured by standard Anti-lock Braking System (ABS) sensors and the measurement of vehicle lateral acceleration obtained from two accelerometers placed diagonally upon the chassis. Similar fusion concept has been employed for development of a kinematic vehicle sideslip angle estimator utilizing information obtained by low-cost inertial sensors and single-antenna GPS receiver. Moreover, a sideslip angle estimator based on vehicle dynamics model with stochastic modeling of the tire forces has been proposed and used for concurrent estimation of other vehicle dynamics variables and parameters, such as the tire sideslip angles, lateral tire forces, tire cornering stiffness, and tire-road coefficient of friction. The research methodology includes: setup of appropriate kinematic and/or dynamic vehicle models; identification, open-loop compensation, and analysis of dominant sources of estimation errors; and design of estimators based on the sensor fusion principle by using the adaptive extended Kalman filter. Verification of the developed estimators has first been carried out by means of computer simulations based on an experimentally verified ten-degrees-of-freedom vehicle dynamics model comprising the magic-formula tire model. In the case of dynamic sideslip angle estimator with stochastic tire modeling, the estimation accuracy has also been verified experimentally, based on the data recorded on a test vehicle equipped with a high-precision inertial measurement unit and two-antenna GPS receiver, as well as by using a standard set of vehicle dynamics control system sensors. In order to obtain a favorable performance of the vehicle state variable estimation under the various operating conditions, a rule-based adaptation of the Kalman filter state covariance matrix has been utilized for kinematic estimators, while for the dynamic, model-based vehicle sideslip angle estimator an adaptive fading algorithm has been implemented for adaptation of the Kalman filter state and measurement covariance matrices.U suvremena vozila ugraÄuje se niz sustava aktivnog upravljanja dinamikom vozila s ciljem poveÄanja sigurnosti i udobnosti vožnje. Ovi sustavi zahtijevaju informacije o varijablama stanja i parametrima dinamike vozila poput brzine skretanja, kuta boÄnog klizanja i kuta valjanja, inercije i mase vozila, statiÄkih karakteristika guma, te informacije o uvjetima na cesti (vrsti podloge tj. koeficijentu trenja kontakta guma-podloga, kutu nagiba ceste i sl.). Neke od ovih varijabli mogu se izravno mjeriti, dok je druge potrebno procijeniti na temelju dostupnih mjerenja i odgovarajuÄih modela kinematike ili dinamike vozila. Intenzivan razvoj raznovrsnih sustava procjene (estimatora) varijabli dinamike vozila motiviran je s jedne strane zahtjevima za smanjenjem potrebnog broja senzora, te s time povezanim smanjenjem cijene sustava upravljanja dinamikom vozila. S druge strane, u posljednje vrijeme javlja se potreba za poboljÅ”anjem performansi konvencionalnih sustava procjene koriÅ”tenjem novih senzorskih tehnologija i kombiniranjem razliÄitih modela estimatora, odnosno primjenom postupaka sažimanja mjerenja viÅ”e razliÄitih senzora. Na taj naÄin, uz odreÄivanje vrijednosti veliÄina koje nije moguÄe ili nije praktiÄno izravno mjeriti, takvi estimatori takoÄer omoguÄuju visoku redundanciju rekonstrukcije varijabli stanja dinamike vozila, te s time povezanu detekciju kvarova senzora i poboljÅ”anje ukupne pouzdanosti cjelokupnog sustava upravljanja dinamikom vozila. Nadalje, sve veÄi broj senzora koji se ugraÄuju u suvremena vozila, kao Å”to su na primjer GPS senzori za navigaciju, inercijski senzori ili inercijske mjerne jedinice (IMU), pružaju nove moguÄnosti u pogledu toÄnijeg i pouzdanijeg odreÄivanja dinamiÄkog ponaÅ”anja vozila. Temeljem dobivenih informacija moguÄe je predvidjeti i sprijeÄiti kritiÄne situacije kao Å”to su proklizavanje kotaÄa, odnosno pojava podupravljanja ili preupravljanja, odnosno gubitka kontrole nad vozilom. Ovaj rad predstavlja prilog istraživanju i razvoju sustava procjene brzine skretanja i kuta boÄnog klizanja vozila zasnovanih na primjeni adaptivnog Kalmanova filtra i naÄela fuzije (sažimanja) senzora. Pritom se razmatra i procjena popratnih parametara dinamike vozila poput gradijenta statiÄke karakteristike autogume za boÄno gibanje i koeficijenta trenja izmeÄu autogume i podloge. Metodologija istraživanja ukljuÄuje postavljanje odgovarajuÄih modela kinematike i dinamike vozila, analizu dominantnih izvora pogreÅ”aka procjene dinamiÄkih varijabli i parametara, te sintezu i simulacijsku i eksperimentalnu provjeru razvijenih sustava procjene (estimatora)
Procjena stanja dinamike vozila zasnovana na fuziji senzora primjenom adaptivnoga Kalmanova filtra
An increasing number of vehicle dynamics control systems are being embedded into modern vehicles in order to assure safety and comfort of driving. All of these systems require information on the vehicle dynamics state variables (e.g. yaw rate, sideslip angle, roll rate etc.). Some of them can be measured, while others need to be estimated based on available measurements and appropriate vehicle kinematics/dynamics models. This thesis presents a contribution to the research of yaw rate and sideslip angle estimation. More specifically, a kinematic sensor fusion-based yaw rate estimator has been proposed, which combines the wheel speeds measured by standard Anti-lock Braking System (ABS) sensors and the measurement of vehicle lateral acceleration obtained from two accelerometers placed diagonally upon the chassis. Similar fusion concept has been employed for development of a kinematic vehicle sideslip angle estimator utilizing information obtained by low-cost inertial sensors and single-antenna GPS receiver. Moreover, a sideslip angle estimator based on vehicle dynamics model with stochastic modeling of the tire forces has been proposed and used for concurrent estimation of other vehicle dynamics variables and parameters, such as the tire sideslip angles, lateral tire forces, tire cornering stiffness, and tire-road coefficient of friction. The research methodology includes: setup of appropriate kinematic and/or dynamic vehicle models; identification, open-loop compensation, and analysis of dominant sources of estimation errors; and design of estimators based on the sensor fusion principle by using the adaptive extended Kalman filter. Verification of the developed estimators has first been carried out by means of computer simulations based on an experimentally verified ten-degrees-of-freedom vehicle dynamics model comprising the magic-formula tire model. In the case of dynamic sideslip angle estimator with stochastic tire modeling, the estimation accuracy has also been verified experimentally, based on the data recorded on a test vehicle equipped with a high-precision inertial measurement unit and two-antenna GPS receiver, as well as by using a standard set of vehicle dynamics control system sensors. In order to obtain a favorable performance of the vehicle state variable estimation under the various operating conditions, a rule-based adaptation of the Kalman filter state covariance matrix has been utilized for kinematic estimators, while for the dynamic, model-based vehicle sideslip angle estimator an adaptive fading algorithm has been implemented for adaptation of the Kalman filter state and measurement covariance matrices.U suvremena vozila ugraÄuje se niz sustava aktivnog upravljanja dinamikom vozila s ciljem poveÄanja sigurnosti i udobnosti vožnje. Ovi sustavi zahtijevaju informacije o varijablama stanja i parametrima dinamike vozila poput brzine skretanja, kuta boÄnog klizanja i kuta valjanja, inercije i mase vozila, statiÄkih karakteristika guma, te informacije o uvjetima na cesti (vrsti podloge tj. koeficijentu trenja kontakta guma-podloga, kutu nagiba ceste i sl.). Neke od ovih varijabli mogu se izravno mjeriti, dok je druge potrebno procijeniti na temelju dostupnih mjerenja i odgovarajuÄih modela kinematike ili dinamike vozila. Intenzivan razvoj raznovrsnih sustava procjene (estimatora) varijabli dinamike vozila motiviran je s jedne strane zahtjevima za smanjenjem potrebnog broja senzora, te s time povezanim smanjenjem cijene sustava upravljanja dinamikom vozila. S druge strane, u posljednje vrijeme javlja se potreba za poboljÅ”anjem performansi konvencionalnih sustava procjene koriÅ”tenjem novih senzorskih tehnologija i kombiniranjem razliÄitih modela estimatora, odnosno primjenom postupaka sažimanja mjerenja viÅ”e razliÄitih senzora. Na taj naÄin, uz odreÄivanje vrijednosti veliÄina koje nije moguÄe ili nije praktiÄno izravno mjeriti, takvi estimatori takoÄer omoguÄuju visoku redundanciju rekonstrukcije varijabli stanja dinamike vozila, te s time povezanu detekciju kvarova senzora i poboljÅ”anje ukupne pouzdanosti cjelokupnog sustava upravljanja dinamikom vozila. Nadalje, sve veÄi broj senzora koji se ugraÄuju u suvremena vozila, kao Å”to su na primjer GPS senzori za navigaciju, inercijski senzori ili inercijske mjerne jedinice (IMU), pružaju nove moguÄnosti u pogledu toÄnijeg i pouzdanijeg odreÄivanja dinamiÄkog ponaÅ”anja vozila. Temeljem dobivenih informacija moguÄe je predvidjeti i sprijeÄiti kritiÄne situacije kao Å”to su proklizavanje kotaÄa, odnosno pojava podupravljanja ili preupravljanja, odnosno gubitka kontrole nad vozilom. Ovaj rad predstavlja prilog istraživanju i razvoju sustava procjene brzine skretanja i kuta boÄnog klizanja vozila zasnovanih na primjeni adaptivnog Kalmanova filtra i naÄela fuzije (sažimanja) senzora. Pritom se razmatra i procjena popratnih parametara dinamike vozila poput gradijenta statiÄke karakteristike autogume za boÄno gibanje i koeficijenta trenja izmeÄu autogume i podloge. Metodologija istraživanja ukljuÄuje postavljanje odgovarajuÄih modela kinematike i dinamike vozila, analizu dominantnih izvora pogreÅ”aka procjene dinamiÄkih varijabli i parametara, te sintezu i simulacijsku i eksperimentalnu provjeru razvijenih sustava procjene (estimatora)