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Open Access Publications from the University of California

Scholarly Works (4 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2014)

This thesis develops vehicle parameter identification algorithms, and applies identified parameters to a controller designed for safe path following.

A tire-road friction coefficient is estimated using an in-tire accelerometer to measure acceleration signals directly from the tires.

The proposed algorithm first determines a tire-road contact patch with a radial acceleration profile.

The estimation algorithm is based on tire lateral deflections obtained from lateral acceleration measurements only inside the contact patch.

A new model is derived for the lateral deflection profiles, which provides robustness to orientation-variation of the accelerometer body frame during tire rotation.

A novel algorithm is developed to identify three inertial parameters: sprung mass, yaw moment of inertia, and longitudinal position of the center of gravity.

A correlation of inertial parameters is derived and is used for the identification algorithm.

Inertial parameters and vehicle states are simultaneously estimated with a dual unscented Kalman filter based on a nonlinear vehicle model.

In order to activate and de-activate different modes of the proposed

algorithm, a local observability analysis is performed with the nonlinear vehicle model.

The performance and robustness of the proposed approach are demonstrated with extensive CarSim simulations and experimental tests on a flat road with a constant tire-road friction coefficient.

Following a curved road can be dangerous if autonomous vehicles do not take roll motion into consideration.

A control algorithm is designed to prevent a dangerous vehicle state induced by roll motion while following a curved road.

Roll motion is suppressed throughout cornering with model predictive control.

A four-wheel nonlinear vehicle model with roll dynamics and a tire brush model are utilized for the prediction of the vehicle state.

An optimal balance in the trade-off between vehicle speed and

roll motion is achieved with full braking as a control actuator.

Identified vehicle inertial parameters are incorporated into the designed controller.

CarSim simulations illustrate the performance of the proposed controller and the effect of the vehicle parameter estimator.

    Cover page: Vehicle Parameter Identification and its Use in Control for Safe Path Following
    • Article
    • Peer Reviewed
    UC San Diego Previously Published Works (2017)
    Myelin basic protein (MBP) is an auto-antigen able to induce intractable pain from innocuous mechanical stimulation (mechanical allodynia). The mechanisms provoking this algesic MBP activity remain obscure. Our present study demonstrates that membrane type 1 matrix metalloproteinase (MT1-MMP/MMP-14) releases the algesic MBP peptides from the damaged myelin, which then reciprocally enhance the expression of MT1-MMP in nerve to sustain a state of allodynia. Specifically, MT1-MMP expression and activity in rat sciatic nerve gradually increased starting at day 3 after chronic constriction injury (CCI). Inhibition of the MT1-MMP activity by intraneural injection of the function-blocking human DX2400 monoclonal antibody at day 3 post-CCI reduced mechanical allodynia and neuropathological signs of Wallerian degeneration, including axon demyelination, degeneration, edema and formation of myelin ovoids. Consistent with its role in allodynia, the MT1-MMP proteolysis of MBP generated the MBP69-86-containing epitope sequences in vitro. In agreement, the DX2400 therapy reduced the release of the MBP69-86 epitope in CCI nerve. Finally, intraneural injection of the algesic MBP69-86 and control MBP2-18 peptides differentially induced MT1-MMP and MMP-2 expression in the nerve. With these data we offer a novel, self-sustaining mechanism of persistent allodynia via the positive feedback loop between MT1-MMP and the algesic MBP peptides. Accordingly, short-term inhibition of MT1-MMP activity presents a feasible pharmacological approach to intervene in this molecular circuit and the development of neuropathic pain.
      Cover page: Reciprocal relationship between membrane type 1 matrix metalloproteinase and the algesic peptides of myelin basic protein contributes to chronic neuropathic pain
      • Article
      • Peer Reviewed
      LBL Publications (2023)
      With South Korea’s electricity demand expected to grow 30% by 2035, transitioning to clean energy resources will be critical in reducing the electric sector emissions and achieving national climate goals. Rapid technological improvements can help keep costs low and maintain grid reliability, if Korea’s government takes a coordinated approach to the clean energy transition. This policy brief identifies key barriers to Korea’s shift toward clean energy, based on the authors’ companion report (A Clean Energy Korea by 2035: Transitioning to 80% Carbon-Free Electricity Generation ), interviews with experts, and the most recent data and literature. It then explores policy solutions for overcoming these technological, economic, and institutional barriers, and suggests market transformation strategies to speed the adoption of clean energy technologies. Amid ongoing cost and technological improvements in wind, solar, and energy storage, advancing this report’s recommended policy actions with maximum coordination among government officials can meaningfully accelerate Korea’s clean energy transition.
        Cover page: Korean Power System Challenges and Opportunities, Priorities for Swift and Successful Clean Energy Deployment at ScaleCreative Commons 'BY-NC-ND' version 4.0 license
        • Article
        • Peer Reviewed
        LBL Publications (2023)
        The current global energy crisis has massive implications for the people and economy of South Korea (Korea), where at least 90% of energy use depends on foreign fossil fuels. Clean electricity accounts for only 39% of total generation, with electricity demand expected to increase 30% by 2035. This study shows that Korea can achieve 80% clean electricity by 2035 by capitalizing on rapid technological improvements and decreasing costs of solar, wind, and battery technology. Doing so would slightly lower electricity supply costs, significantly reduce dependence on imported natural gas and coal, and dramatically cut power sector emissions. Further, this study finds that Korea’s power grid under a clean energy scenario will maintain reliability without coal generation or new natural gas plants. To realize these significant economic, environmental, and energy security benefits, policies such as an 80% clean electricity standard by 2035 and corresponding renewable energy deployment goals are required.
          Cover page: A Clean Energy Korea by 2035, Transitioning to 80% Carbon-free Electricity GenerationCreative Commons 'BY-NC-ND' version 4.0 license
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