Yiran Hu

Model-based calibration for battery characterization in HEV applications

In hybrid electric vehicle (HEV) applications, unlike electric vehicles, operation with the battery system requires control in a relatively limited range of state-of-charge (SoC), where best efficiency, gradual aging, and no self-damaging operations are expected. In this context, one of the main, critical technical challenges is the estimation of the SoC under vehicle operations, which typically do not involve full charging or discharging. This task is particularly arduous to accomplish in real-time, due to the complex and nonlinear behavior of the battery, as well as the inevitable presence of on-board measurement errors. In this work, we describe a model-based calibration process for capturing the important characteristics of modern batteries used in typical HEV applications. This process consists of reproducible procedural steps, including pre-specified data collection, while ultimately admitting a calibration. The resulting models are useful in HEV system control design for algorithms centered on maintaining the battery SoC, in algorithms for prognostics and diagnostics, and in prediction and estimation tasks.

Total engine optimization and control for SI engines using linear parameter-varying models

The role that supervisory control or upper-level multi-objective optimization can play in total engine control is considered. This involved the control of an SI engine for a combination of air-fuel ratio, torque, fuel consumption and residual gas fraction. The upper level optimization algorithm, based on Model Predictive Control principles, makes use of a ‘reference model.’ This is constructed as a closed-loop interconnection of the engine model and the lower-level classical torque/air charge and lambda controller. This model is derived in a linear parameter varying form, which facilitates the application of the predictive control law. The main contribution is the proposed hierarchical control structure, which has been assessed in simulation and on a test track, and provides a useful separation in tasks and functionality. The solution is also compared briefly with MPC at both upper and lower levels, using different sample rates.