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    Zijin Longking 230 t battery truck and EACON deal: haulage design notes for engineers

    August 11, 2026|

    Reviewed by Tom Sullivan

    First reported on International Mining – News

    30 Second Briefing

    Zijin Longking has launched the ZL230E, a 230 t class pure battery-electric mining truck (formerly LK350E) in Longyan, Fujian, claimed as the largest-tonnage pure electric unit currently available. The rollout coincided with an investment promotion event for the “Mining + Intelligent Manufacturing” cluster in Xinluo District, signalling intent to localise large-scale electric haulage manufacturing. Zijin Longking also signed an autonomy partnership with Chinese OEM-agnostic automation specialist EACON, paving the way for future driverless deployment of the ZL230E fleet.

    Technical Brief

    • Rollout and investment promotion event held 10 August 2026 in Longyan City, Fujian Province.
    • ZL230E designation replaces earlier LK350E model name in Zijin Longking’s product line.
    • Event framed within Xinluo District’s “Mining + Intelligent Manufacturing” industrial cluster development programme.

    Our Take

    Zijin Longking’s move from the earlier LK220E units (May 2026 dispatch from Longyan City) to a 230 t-class truck suggests it is quickly scaling up payload classes, positioning Fujian as a base for large-format battery haulage manufacturing rather than just pilot-scale output.

    EACON’s ORCASTRA platform is already running mixed-energy fleets in Xinjiang and cabless AT-150 trucks at SPIC’s South coal mine, so integrating a 230 t pure battery truck gives it a reference portfolio that spans both mid-size and ultra-class autonomous haulage in China.

    With EACON’s recent HKEX listing raising about HK$2.3 billion for autonomous haulage expansion, this partnership with Zijin Longking in Fujian Province is likely to channel some of that capital into scaling software-hardware integration on domestically built ultra-class electric trucks.

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    Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.

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