{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:CUTLT2644B6N26RE64KD6VH2D4","short_pith_number":"pith:CUTLT264","schema_version":"1.0","canonical_sha256":"1526b9ebdce07cdd7a24f7143f54fa1f2ead239fdebc16bde6559d051bd50d48","source":{"kind":"arxiv","id":"2306.08823","version":2},"attestation_state":"computed","paper":{"title":"Plug-in Hybrid Electric Vehicle Energy Management with Clutch Engagement Control via Continuous-Discrete Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Changfu Gong, Jinming Xu, Yuan Lin","submitted_at":"2023-06-15T02:35:15Z","abstract_excerpt":"Energy management strategy (EMS) is a key technology for plug-in hybrid electric vehicles (PHEVs). The energy management of certain series-parallel PHEVs involves the control of continuous variables, such as engine torque, and discrete variables, such as clutch engagement/disengagement. We establish a control-oriented model for a series-parallel plug-in hybrid system with clutch engagement control from the perspective of mixed-integer programming. Subsequently, we design an EMS based on continuous-discrete reinforcement learning (CDRL), which enables simultaneous output of continuous and discr"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2306.08823","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2023-06-15T02:35:15Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"2da794d193b6d159ddfe5aa290499c222527c5b080910140d95f3de190615513","abstract_canon_sha256":"d44133cf3f13db7a9b12c50d8f3849ba67c3aed61d7fa4d91286c804197a20db"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:51:09.441960Z","signature_b64":"wcgP0DnRJzRrlK54MvoHPEyQ6xLLKprWMf3YpZHaf4H9LnzUnuawM7NHXrmnetv2kuEBupPZjyZcO+kSyLLCCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1526b9ebdce07cdd7a24f7143f54fa1f2ead239fdebc16bde6559d051bd50d48","last_reissued_at":"2026-07-05T07:51:09.441393Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:51:09.441393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Plug-in Hybrid Electric Vehicle Energy Management with Clutch Engagement Control via Continuous-Discrete Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Changfu Gong, Jinming Xu, Yuan Lin","submitted_at":"2023-06-15T02:35:15Z","abstract_excerpt":"Energy management strategy (EMS) is a key technology for plug-in hybrid electric vehicles (PHEVs). The energy management of certain series-parallel PHEVs involves the control of continuous variables, such as engine torque, and discrete variables, such as clutch engagement/disengagement. We establish a control-oriented model for a series-parallel plug-in hybrid system with clutch engagement control from the perspective of mixed-integer programming. Subsequently, we design an EMS based on continuous-discrete reinforcement learning (CDRL), which enables simultaneous output of continuous and discr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.08823","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2306.08823/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2306.08823","created_at":"2026-07-05T07:51:09.441459+00:00"},{"alias_kind":"arxiv_version","alias_value":"2306.08823v2","created_at":"2026-07-05T07:51:09.441459+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.08823","created_at":"2026-07-05T07:51:09.441459+00:00"},{"alias_kind":"pith_short_12","alias_value":"CUTLT2644B6N","created_at":"2026-07-05T07:51:09.441459+00:00"},{"alias_kind":"pith_short_16","alias_value":"CUTLT2644B6N26RE","created_at":"2026-07-05T07:51:09.441459+00:00"},{"alias_kind":"pith_short_8","alias_value":"CUTLT264","created_at":"2026-07-05T07:51:09.441459+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4","json":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4.json","graph_json":"https://pith.science/api/pith-number/CUTLT2644B6N26RE64KD6VH2D4/graph.json","events_json":"https://pith.science/api/pith-number/CUTLT2644B6N26RE64KD6VH2D4/events.json","paper":"https://pith.science/paper/CUTLT264"},"agent_actions":{"view_html":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4","download_json":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4.json","view_paper":"https://pith.science/paper/CUTLT264","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2306.08823&json=true","fetch_graph":"https://pith.science/api/pith-number/CUTLT2644B6N26RE64KD6VH2D4/graph.json","fetch_events":"https://pith.science/api/pith-number/CUTLT2644B6N26RE64KD6VH2D4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4/action/storage_attestation","attest_author":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4/action/author_attestation","sign_citation":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4/action/citation_signature","submit_replication":"https://pith.science/pith/CUTLT2644B6N26RE64KD6VH2D4/action/replication_record"}},"created_at":"2026-07-05T07:51:09.441459+00:00","updated_at":"2026-07-05T07:51:09.441459+00:00"}