A 42-V powernet has been recognized as the next generation of vehicle electrical systems, and the waste-heat thermoelectric generator is becoming the future of vehicular energy conservation and emission reduction technologies. In this paper, effective utilization of vehicular waste-heat energy is proposed by introducing an electrical and hybrid driving system, which is an assemblage of a waste-heat thermoelectric generator, a 42-V powernet, and an integrated starter and generator (ISG). A vehicle model and the submodels for the new system have been built on the ADVISOR platform based on MATLAB/Simulink, and the dynamic performance of the vehicle model tested using the Economic Commission for Europe–Europe Urban Dynamometer Cycle driving cycle. The simulation results indicate that application of a 42-V waste-heat thermoelectric vehicle could be an integrated approach for fuel economy improvement and emission reduction, compared with a conventional internal combustion engine vehicle and an ISG-type 42-V vehicle.

A 42-V Electrical and Hybrid Driving System Based on a Vehicular Waste-Heat Thermoelectric Generator

A Vehicle Control Unit (VCU) apparatus and method for controlling the elements of a Hybrid Electric Drive Powered Vehicle are disclosed, wherein the VCU uses Current and Historical Route Data to determine Instantaneous Power required by each of the elements, and wherein the VCU controls the Instantaneous Power used by each of the elements to minimize an amount of hydrocarbon fuel used while the vehicle is being driven, while also maintaining an acceptable battery state of charge and providing vehicle drive power as needed.

Method and apparatus for a vehicle control unit (VCU), using current and historical instantaneous power usage data, to determine optimum power settings for a hybrid electric drive system

Optimization of the control strategy plays an important role in improving the performance of electric vehicles. In order to improve the braking stability and recover the braking energy, a multi-obj...

https://journals.sagepub.com/doi/pdf/10.1177/1687814014568491

Multi-objective optimization of the control strategy of electric vehicle electro-hydraulic composite braking system with genetic algorithm

Downshift decision and process optimal control of dual clutch transmission for hybrid electric vehicles under rapid braking condition

This paper proposes a constrained optimization-based torque control allocation method aimed to improve energy efficiency, and thus, driving range for electric vehicles. In the proposed method, the cost function is defined not only to achieve desired yaw moment for vehicle handling and stability, but also to minimize power losses for energy efficiency. The particular attention is paid to the power losses due to tire slips both longitudinally and laterally. The constraints are also set based on thorough investigation on various causes of power disppation such that the torque is allocated with restraint to use regenerative braking in its maximum capacity. The proposed control allocation method has been tested and verified to be effective on energy efficiency improvement through both simulation and experiment under various driving maneuvers.

Torque control allocation based on constrained optimization with regenerative braking for electric vehicles

A novel regenerative braking algorithm based on regenerative torque optimization with emulate engine compression braking (EECB) was proposed to make effective and maximum use of brake energy in order to improve fuel economy. The actual brake oil pressure of driving wheel which is reduced by the amount of the regenerative braking force is supplied from the electronic hydraulic brake system. Regenerative torque optimization maximizes the actual regenerative power recuperation by energy storage component, and EECB is a useful extended type of regenerative braking. The simulation results show that actual regenerative power recuperation for the novel regenerative braking algorithm is more than using conventional one, and life-span of brake disks is prolonged for the novel algorithm.

Wen-yong Xiao

Papers

Regenerative braking algorithm for an ISG HEV based on regenerative torque optimization