Huei Peng

Power management strategy for a parallel hybrid electric truck

Hybrid vehicle techniques have been widely studied recently because of their potential to significantly improve the fuel economy and drivability of future ground vehicles. Due to the dual-power-source nature of these vehicles, control strategies based on engineering intuition frequently fail to fully explore the potential of these advanced vehicles. In this paper, we present a procedure for the design of a near-optimal power management strategy. The design procedure starts by defining a cost function, such as minimizing a combination of fuel consumption and selected emission species over a driving cycle. Dynamic programming (DP) is then utilized to find the optimal control actions including the gear-shifting sequence and the power split between the engine and motor while subject to a battery SOC-sustaining constraint. Through analysis of the behavior of DP control actions, near-optimal rules are extracted, which, unlike DP control signals, are implementable. The performance of this power management control strategy is studied by using the hybrid vehicle model HE-VESIM developed at the Automotive Research Center of the University of Michigan. A tradeoff study between fuel economy and emissions was performed. It was found that significant emission reduction could be achieved at the expense of a small increase in fuel consumption.

Automated vehicle control developments in the PATH program

The accomplishments to date on the development of automatic vehicle control technology in the Program on Advanced Technology for the Highway (PATH) at the University of California, Berkeley, are summarized. The basic principles and assumptions underlying the PATH work are identified, and the work on automating vehicle lateral (steering) and longitudinal (spacing and speed) control is explained. For both lateral and longitudinal control, the modeling of plant dynamics is described, and the development of the additional subsystems needed (communications, reference/sensor systems) and the derivation of the control laws are presented. Plans for testing on vehicles in both near and long term are discussed. >

Modeling and Control of a Power-Split Hybrid Vehicle

Toyota hybrid system (THS) is used in the current best selling hybrid vehicle on the market-the Toyota Prius. This hybrid system contains a power-split planetary gear system which combines the benefits of series and parallel hybrid vehicles. In this paper, we developed a dynamic model of the THS powertrain and then apply it for model-based control development. Two control algorithms are introduced: one based on the stochastic dynamic programming method, and the other based on the equivalent consumption minimization strategy. Both approaches determine the engine power based on the overall vehicle efficiency and apply the electrical machines to optimize the engine operation. The performance of these two algorithms is assessed by comparing against the dynamic programming results, which are non-causal but provide theoretical benchmarks for other implementable control algorithms.

Optimal Control of Hybrid Electric Vehicles Based on Pontryagin's Minimum Principle

A number of strategies for the power management of hybrid electric vehicles (HEVs) are proposed in the literature. A key challenge is to achieve near-optimality while keeping the methodology simple. The Pontryagins minimum principle (PMP) is suggested as a viable real-time strategy. In this brief, the global optimality of the principle under reasonable assumptions is described from a mathematical viewpoint. Instantaneous optimal control with an appropriate equivalent parameter for battery usage is shown to be possibly a global optimal solution under the assumption that the internal resistance and open-circuit voltage of a battery are independent of the state-of-charge (SOC). This brief also demonstrates that the optimality of the equivalent consumption minimization strategy (ECMS) results from the close relation of ECMS to the optimal-control-theoretic concept of PMP. In static simulation for a power-split hybrid vehicle, the fuel economy of the vehicle using the control algorithm proposed in this brief is found to be very close-typically within 1%-to the fuel economy through global optimal control that is based on dynamic programming (DP).

Control of fuel cell breathing

In this article we analyzed and designed air flow controllers that protect the fuel cell (FC) stack from oxygen starvation during step changes of current demand. The steady-state regulation of the oxygen excess ratio in the FCS cathode achieved by assigning an integrator to the compressor flow. Linear observability techniques were employed to demonstrate improvements in transient oxygen regulation when the FCS voltage is included as a measurement for the feedback controller. The FCS voltage signal contains high frequency information about the FC oxygen utilization, and thus, is a natural and valuable output for feedback. We used linear optimal control design to identify the frequencies at which there is a severe tradeoff between the transient system net power performance and the stack starvation control. The limitation arises when the FCS system architecture dictates that all auxiliary equipment is powered directly from the FC with no secondary power sources. This plant configuration is preferred due to its simplicity, compactness, and low cost. The FCS impedance given the closed-loop air flow and perfect humidification and temperature regulation captures the FC current-voltage dynamic relationship. It is expected that the closed-loop FCS impedance will provide the basis for the systematic design of FC stack electronic components.

Control-oriented modeling and analysis for automotive fuel cell systems

Fuel Cells are electrochemical devices that convert the chemical energy of a gaseous fuel directly into electricity. They are widely regarded as a potential future stationary and mobile power source. The response of a fuel cell system depends on the air and hydrogen feed, flow and pressure regulation, and heat and water management. In this paper, we develop a dynamic model suitable for the control study of fuel cell systems. The transient phenomena captured in the model include the flow and inertia dynamics of the compressor, the manifold filling dynamics (both anode and cathode), reactant partial pressures, and membrane humidity. It is important to note, however, that the fuel cell stack temperature is treated as a parameter rather than a state variable of this model because of its long time constant. Limitations and several possible applications of this model are presented.

Recursive least squares with forgetting for online estimation of vehicle mass and road grade: theory and experiments

Good estimates of vehicle mass and road grade are important in automation of heavy duty vehicles, vehicle following manoeuvres or traditional powertrain control schemes. Recursive least square (RLS) with multiple forgetting factors accounts for different rates of change for different parameters and thus, enables simultaneous estimation of the time-varying grade and the piece-wise constant mass. An ad hoc modification of the update law for the gain in the RLS scheme is proposed and used in simulation and experiments. We demonstrate that the proposed scheme estimates mass within 5% of its actual value and tracks grade with good accuracy provided that inputs are persistently exciting. The experimental setups, signals, their source and their accuracy are discussed. Issues like lack of persistent excitations in certain parts of the run or difficulties of parameter tracking during gear shift are explained and suggestions to bypass these problems are made.

Differential-Braking-Based Rollover Prevention for Sport Utility Vehicles with Human-in-the-loop Evaluations

An anti-rollover control algorithm based on the Time-To-Rollover (TTR) metric is proposed in this paper. A simple model with steering and direct yaw moment control inputs was constructed to calculate the TTR in real-time. The TruckSim dynamic simulation software was used to verify the control performance, as well as to simulate the system dynamics in the UM-Oakland driving simulator. Both the simple and complex (TruckSim) models were tuned to match the behavior of a 1997 Jeep Cherokee vehicle with lateral acceleration up to 0.6 g. The performance of the proposed control system was compared with other threshold-based rollover-prevention control algorithms. Finally, a human-in-the-loop experiment was conducted to study the performance of the proposed algorithm under more realistic driving conditions.

Modeling and control for PEM fuel cell stack system

A nonlinear fuel cell system dynamic model that is suitable for control study is presented. The transient phenomena captured in the model include the flow characteristics and inertia dynamics of the compressor, the manifold filling dynamics, and consequently, the reactant partial pressures. Characterization of the fuel cell polarization curves based on time varying current, partial oxygen and hydrogen pressures, temperature, membrane hydration allows analysis and simulation of the transient fuel cell power generation. An observer based feedback and feedforward controller that manages the tradeoff between reduction of parasitic losses and fast fuel cell net power response during rapid current (load) demands is designed.

Current Management in a Hybrid Fuel Cell Power System: A Model-Predictive Control Approach

The problem of oxygen starvation in fuel cells coupled with air compressor saturation limits, is addressed in this paper. We propose using a hybrid configuration, in which a bank of ultracapacitors supplements the polymer electrolyte membrane fuel cell during fast current transients. Our objective is to avoid fuel cell oxygen starvation, prevent air compressor surge and choke, and simultaneously match an arbitrary level of current demand. We formulate the distribution of current demand between the fuel cell and the bank of ultracapacitors in a model predictive control framework, which can handle multiple constraints of the hybrid system. Simulation results show that reactant deficit during sudden increase in stack current is reduced from 50% in stand-alone architecture to less than 1% in the hybrid configuration. In addition, the explicit constraint handling capability of the current management scheme prevents compressor surge and choke and maintains the state-of-charge of the ultracapacitor within feasible bounds