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    Yutong’s 100 BEV trucks at Baoqing Chaoyang: performance insights for mine planners

    July 28, 2026|

    Reviewed by Tom Sullivan

    Yutong’s 100 BEV trucks at Baoqing Chaoyang: performance insights for mine planners

    First reported on International Mining – News

    30 Second Briefing

    Yutong reports that 100 of its battery electric wide-body mining trucks are now in stable, large-scale operation at the Baoqing Chaoyang open-pit lignite mine in Heilongjiang’s sub‑zero winter conditions. The mine, with over 800 Mt of proven reserves, is using the BEV fleet for overburden and coal haulage under complex topography, supporting China’s dual‑carbon strategy by displacing conventional diesel units. For mine planners and fleet engineers, the deployment signals growing operational confidence in high‑capacity BEVs in cold‑climate, large open‑pit coal operations.

    Technical Brief

    • Deployment is at Baoqing Chaoyang open-pit lignite mine in Shuangyashan, Heilongjiang Province.
    • Lignite deposit exceeds 800 Mt of proven reserves, supporting long-term fleet utilisation planning.
    • Operation forms part of China’s dual-carbon policy push for lower-emission domestic coal production.

    Our Take

    Yutong’s 100-unit battery electric truck deployment at the Baoqing Chaoyang open-pit coal mine sits alongside its growing mine-spec bus footprint in Australia, where related coverage shows VDI has already delivered 2,000 Yutong mining buses into operations such as Rio Tinto’s Pilbara sites, signalling that the OEM is building parallel positions in both haulage and personnel transport for large-scale mines.

    In our database of Mining–Sustainability pieces tagged to coal and lignite, most decarbonisation coverage still centres on power generation or automation; a 100-strong BEV truck fleet in China marks a notable shift towards tackling Scope 1 emissions in the extraction phase itself, which could pressure diesel haulage at other large lignite and coal pits to demonstrate comparable cost and uptime performance.

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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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