US-20260125042-A1 - Software-Defined Hybrid Powertrain and Vehicle

US20260125042A1US 20260125042 A1US20260125042 A1US 20260125042A1US-20260125042-A1

Abstract

A dual-motor mixed-hybrid powertrain system, by performing digital pulse control (DPC) on the instantaneous power time-varying functions of an engine and a battery pack, can convert the complex surface-working-condition of an analog-electronic-control (AEC) engine in the existing technology into a simpler pre-defined line-working-condition of a DPC engine, multiplexing in time either a pre-defined high-state line-working-condition in the combustion high-efficiency zone or a pre-defined non-combustion low-state line-working-condition with zero fuel consumption and zero pollutant emissions, achieving decoupling between a DPC engine working condition and the overall vehicle working condition and decoupling between software and hardware of a hybrid powertrain. By software defining and over-the-air updating, the vehicle power management strategy can be customized quickly for each vehicle or transport event, to achieve online energy-saving and emission-reduction simultaneous global optimization under the premise of industry leading vehicle power and braking performance and full customization of a thousand vehicle and a thousand face.

Inventors

Wangjie Gesang
Wei Cha

Assignees

Wangjie Gesang
Wei Cha
LCB INTERNATIONAL INC.

Dates

Publication Date: 20260507
Application Date: 20251229
Priority Date: 20210205

Claims (14)

1 . A method to implement a hybrid vehicle predictive power-management-strategy (PPMS) based on a digital-pulse-control (DPC) method, wherein the hybrid vehicle comprises: an engine, a traction motor (MG2) connected to a transmission box, an electric power-splitting-device (ePSD), at least one high-power battery pack supplying electric power to the traction motor through the ePSD, a clutch placed between the engine and the traction motor, a vehicle controller (VCU) configured to make the hybrid vehicle, under normal operations, to operate stably in parallel-hybrid mode; wherein the DPC method comprises: a sub-second-level fast-control-loop for instantaneous power functions and another minute-level slow-control-loop for average power functions, the fast-control-loop includes at least a series-hybrid intelligent stop-start (iSS) control or a parallel-hybrid intelligent power-switch (iPS) control of the instantaneous power functions of the engine and the battery pack, the slow-control-loop includes a predicative state-of-charge (SoC) control (PSC) of the battery pack, wherein the fast-control-loop and the slow-control-loop are decoupled and can be controlled independently to ensure the DPC engine and the battery pack to operate stably in the respective high efficiency zones almost always and independent of the working condition of the hybrid vehicle; wherein: in the fast-control-loop, applying the intelligent stop-start (ISS) control when the hybrid vehicle operates stably in series-hybrid mode or the intelligent power-switch (IPS) control when the hybrid vehicle operates stably in parallel-hybrid mode, thereby transforming the engine instantaneous power function from an analogue time-varying function into a bi-polar pulse-width-modulation (PWM) time series function, at the same time directing the instantaneous power function of the battery pack to track the difference-function between the hybrid vehicle road-load instantaneous power function and the DPC engine instantaneous power function in real-time to satisfy the vehicle dynamic equation and the series-hybrid or parallel-hybrid power balance equation; in the slow-control-loop, the PSC method contains the following steps: (i) within the electronic horizon, setting the vehicle nominal cruising speed dynamically, computing on-vehicle quickly and continuously the function-distributions of the vehicle road-load instantaneous power and average power according to the vehicle dynamic equation, the moving average equation, the hybrid vehicle parameters and dynamic operational data; (ii) predictively shaping the difference-function-distribution between the vehicle road-load average power function-distribution and the engine average power function-distribution through independent and dynamic adjustment of the DPC engine duty-cycle and tracking the difference-function in real-time through charging or discharging of the battery pack in order to satisfy the series-hybrid or parallel-hybrid power balance equation, controlling the battery pack to operate stably in one out of three modes of charge-sustaining (CS), charge-depleting (CD), and charge-increasing (CI) or to switch dynamically among these three modes, thereby ensuring the battery pack to operate stably in its high-efficiency zone most of the time and to maximize its regen charge turnover rate for any transport event; (iii) when the absolute value of the average power difference-function-distribution is always less than a pre-set positive threshold, the battery pack operates stably in the charge-sustaining mode (CS); when the difference-function-distribution is mostly larger than a pre-set positive threshold and always lager than zero, the battery pack operates stably in the charge-depletion mode (CD); when the difference-function-distribution is mostly less than a pre-set negative threshold and always less than zero, the battery pack operates stably in the charge-increasing mode (CI).
2 . The method of claim 1 , wherein the hybrid vehicle further comprises: a generator (MG1) placed in the hybrid P1 position and connected with the engine mechanically to form the generator-set, the traction motor (MG2) placed in one of the following four hybrid positions of P2, P2.5, P3, P4, the vehicle controller (VCU) configured to make the hybrid vehicle, under normal operations, to operate stably only in either series-hybrid mode or parallel-hybrid mode; wherein the DPC method further comprises: an intelligent mode-switching control (iMS) and a parallel-hybrid clutch-less gear-shift (CGS) control; the iMS method includes the following steps; (i) within the electronic horizon, presetting the vehicle nominal cruising speed dynamically, computing on-vehicle quickly and continuously the vehicle road-load instantaneous power and average power function-distributions according to the vehicle dynamic equation, the moving average equation, the hybrid vehicle parameters and dynamic operational data; (ii) along a road section within the electronic horizon where the absolute value of the vehicle road-load average power function-distribution is consistently less than a pre-set threshold, the hybrid vehicle is directed to operate stably in series-hybrid mode with the iSS control, along the rest of the road within the electronic horizon, the hybrid vehicle is directed to operate stably in parallel-hybrid mode with the iPS control; (iii) when the hybrid vehicle is switched between the series-hybrid mode and the parallel-hybrid mode bidirectionally, firstly the DPC engine is directed to operate stably in a pre-defined low-state and the hybrid vehicle is powered by the traction motor, the generator and/or the traction motor individually or collaboratively to accomplish torque-interruption and rotation-speed-synchronizations at the clutch, secondly the DPC engine is allowed to resume operation in a pre-defined high-state with a second-level time buffer after the clutch completes the switching operation between series-hybrid and parallel-hybrid; the CGS method includes the following steps: (iv) applying the parallel-hybrid iPS control and keeping the clutch closed constantly; (v) directing the DPC engine to operate stably in the low-state before the start of a transmission gear shift, using one of the following three options of the generator, the traction motor, or the generator and the traction motor to achieve torque-interruption and rotation-speed-synchronization between the engine flywheel and the transmission input shaft, then completing a smooth gear shift of the transmission; (vi) after the completion of the transmission gear shift, the DPC engine being allowed to resume operation in the high-state.
3 . The method of claim 1 , wherein the hybrid vehicle further comprises: the engine being a near-zero-emission diesel engine with variable-valve-actuation (VVA) mechanism for all the intake/exhaust valves, an electric catalyst heater (ECH), a selective-catalytic-reduction (SCR) module, an engine after-treatment system containing the ECH and the SCR capable of meeting at least one of the following emission standards of EPA-2027, Euro-VII, or GB-7; wherein the DPC method further comprises: a binary-cylinder-deactivation (bCDA) method or a clean-cold-start (CCS) method; the bCDA method includes the following steps: (i) during the DPC engine high-state stable operations, all the cylinders and intake/exhaust valves of the engine remain in normal operations; (ii) during most of the DPC engine low-state stable operations, all the cylinders of the engine are deactivated with fuel cut-off and all the intake/exhaust valves of the engine remain closed constantly, at this time the DPC engine has a duty-cycle of 0 and is in a low-state full-deactivation-operation to further reduce the engine pumping loss and to enhance the thermal management of the engine after-treatment system; (iii) the DPC engine must maintain a low-state normal operation time-buffer of at least one full-engine-cycle before the DPC engine is switched bi-directionally between the low-state full-deactivation-operation and the high-state operation; (iv) the DPC engine with the bCDA function has at least one independent control channel to switch bi-directionally all the intake/exhaust valves of the engine between the low-state normal operation and the low-state full-deactivation-operation; the CCS method includes the following steps: (i) the VCU with automatic wake-up function applies the series-hybrid iSS control or the parallel-hybrid iPS control to the parked hybrid vehicle according to a pre-set wake-up time for each working-day; (ii) if the parked hybrid vehicle is under parallel-hybrid iPS control, then the transmission must be in neutral; (iii) during the parked vehicle clean warm-up period, the VCU directs the DPC engine to operate stably in the low-state at a predefined rotation speed and the battery pack to operate stably in charge-depletion mode, the battery pack also provides electric power to the ECH to heat-up the SCR module to light-off temperature in minute-level time, then the DPC engine is allowed to operate stably in the high-state to charge the battery pack for the first time in a working-day for at least sub-minute level before the parked hybrid vehicle is allowed to run.
4 . The method of claim 1 , further comprising: configuring the VCU to implement a rule-based or an optimization-based predicative power-management-strategy of the hybrid vehicle by executing in real-time a known fuel-saving algorithm and producing an instantaneous power function-distribution of the DPC engine and a RDE fuel consumption for the transport event; the DPC method uses the duty-cycle of the DPC engine as the leading control variable to enhance the convergence rate and robustness and to reduce the on-vehicle computing power or memory requirements of any fuel-saving algorithm for the hybrid vehicle; the resulting RDE fuel consumption is very close to the global minimum value for any transport event with low spread and is essentially decoupled from the hybrid vehicle powertrain parameters or the human driver.
5 . The method of claim 1 , further comprising: configuring the VCU to implement a machine-learning-based (ML) predicative power-management-strategy of the hybrid vehicle by transforming the hybrid vehicle energy-saving emission-reduction optimal-control problem into an equivalent AI problem of computer playing Go, to download a trained ML model from a cloud-computing-platform, to execute in real-time a known fuel-saving algorithm based on the trained ML model, and to produce an optimal instantaneous power function-distribution of the DPC engine and a RDE fuel consumption for the transport event; the DPC method uses the duty-cycle of the DPC engine as the leading control variable to enhance the convergence rate and robustness and to reduce the on-vehicle computing power or memory requirements of any fuel-saving algorithm; the resulting RDE fuel consumption can achieve the global minimum value for any transport event in the engineering sense with low spread and is essentially decoupled from the hybrid vehicle powertrain parameters or the human driver.
6 . The method of claim 1 , wherein at least one of the following conditions is satisfied: (i) the fast-control-loop has a time scale of sub-second-level; (ii) the slow-control-loop has a time scale of minute-level; (iii) the electronic horizon has a time scale of hour-level or a distance scale of hundred-kilometer-level; (iv) the moving-average computation time-window is larger than the PWM period, and both have the time scale of minute-level when converting an instantaneous-power function into a corresponding average-power function; (v) the moving-average computation time-window is much smaller than the PWM period and is in the range of 1-15 seconds when converting an instantaneous SoC function into a corresponding average SoC function; (vi) when computing the vehicle road-load instantaneous or average power function-distribution in the electronic horizon, the time-step is at second-level and the power function granularity is at kW-level; (vii) in each PWM period, the DPC engine can have at most one jump-down from high-state to low-state and one jump-up from low-state to high-state, and the transition time of jump-up is larger than that of jump-down and both are at second-level; (viii) the output of the fuel-saving algorithm contains in-essence a nonunique optimal DPC engine duty-cycle time-varying function-distribution for the transport event.
7 . The method of claim 1 , wherein a fuel-saving data-set of the hybrid vehicle is collected and stored on-vehicle quickly and continuously with second-level refreshing time-step throughout a transport event; the fuel-saving data-set comprises at least one group of the following time-varying function-distributions of the hybrid vehicle for the transport event: 1) vehicle speed plus geographical location and road grade, 2) DPC engine rotation speed and duty-cycle, 3) battery pack SoC as well as the charging or discharging DC voltage and total current, 4) accelerator or brake pedal control signal, 5) vehicle nominal cruising speed; the fuel-saving data set further comprises at least one of the following static parameters of the hybrid vehicle for the transport event: the total vehicle weight and frontal area, vehicle air-drag coefficient and tire rolling friction coefficient, DPC engine pre-defined high-state and low-state working-condition lines, the universal characteristics of the generator or traction motor, the charging-discharging characteristics of the battery pack; the fuel-saving data-set is uploaded from the hybrid vehicle to a cloud computing platform on the Internet timely for future use.
8 . A hybrid vehicle, comprising: an engine, a traction motor mechanically connected to a transmission box, at least one high-power battery pack supplying the electric power to the traction motor through an electric power-splitting device (ePSD), a clutch placed between the engine and the traction motor; under normal operations, the hybrid vehicle operates stably in parallel-hybrid mode; a vehicle controller (VCU) configured to implement the method according to claim 1 for the hybrid vehicle predictive power-management-strategy (PPMS) based on the digital pulse control (DPC) method in order to optimize the hybrid vehicle RDE fuel-consumption and pollutant-emissions for any transport event.
9 . The hybrid vehicle of claim 8 , further comprising: a generator set containing a generator placed in the hybrid P1 position mechanically connected to the engine, wherein the generator set is connected to the traction motor through the clutch and supplies electric power to at least the battery-pack or the traction-motor through the ePSD; the traction motor is placed in one of the following hybrid positions of P2, P2.5, P3, P4; under normal operations, the hybrid vehicle only operates stably in either series-hybrid or parallel-hybrid mode; the VCU is further configured to optimize the hybrid vehicle RDE fuel-consumption and pollutant-emissions for any transport event.
10 . The hybrid vehicle of claim 8 , further comprising: an electric catalyst heater (ECH), a selective-catalytic-reduction (SCR) module, an engine after-treatment system containing the ECH and the SCR, the engine with variable-valve actuation mechanism for all its intake/exhaust valves and a corresponding control software; the VCU is configured to achieve RDE near-zero-emissions and to optimize the hybrid vehicle RDE fuel-consumption and pollutant-emissions for any transport event.
11 . The hybrid vehicle of claim 8 , wherein at least one of the following conditions is satisfied: (i) further comprising at least one of the following sub-systems: a satellite navigation unit (GNSS), a map unit (MU), a telecommunication box, a millimeter microwave radar (mWR); (ii) the ePSD further contains a DC voltage-controlled-switch (VCS) and the VCS is externally connected with a high-power braking-resistor at the port III of the ePSD; (iii) the VCU is a 32-bit or 64-bit embedded micro-controller or further includes an AI processor for on-vehicle AI inference computation; (iv) the VCU contains at least 2 independent CAN channels, at least one CAN channel is compliant with the SAE J1939 protocol.
12 . The hybrid vehicle of claim 8 , wherein at least one of the following conditions is satisfied: (i) the hybrid vehicle is a Class 7 or 8 heavy-truck primarily used for long-haul freight; (ii) the engine displacement of the hybrid vehicle is in the range of 6 L-17 L and the engine peak-power is in the range of 175-510 kW; (iii) the transmission box of the hybrid vehicle is an automated-mechanical-transmission (AMT) with at least 5 forward speeds and a maximum input torque over 2600 NM.
13 . The hybrid vehicle of claim 8 , wherein at least one of the following conditions is satisfied: (i) the generator and the traction motor are low-speed and high-torque permeant-magnetic-synchronous-motors (PMSM) or AC motors, each having a rated power over 100 KW; (ii) the battery pack has a total capacity in the range of 10-200 kWh with or without on-board charging capability; (iii) the rated DC voltage at the junction point X of the ePSD is on a 800V-platform.
14 . The hybrid vehicle of claim 8 , further comprising: wherein the ePSD is a power-electronics network and contains a motor-controller for the generator (MCU1) and another motor-controller for the traction motor (MCU2); the DC ends of the MCU1 and MCU2 are connected to the DC bus junction point X, the AC end of MCU1 or MCU2 is connected to the generator or the traction motor respectively; the ePSD further comprises at least a DC-DC converter or a voltage-controlled-switch (VCS), wherein one end of the DC-DC converter or the VCS is connected to the DC bus junction point X, the other end of the DC-DC converter is connected to the battery pack, and the other end of the VCS is connected to a braking-resistor, both the battery pack and the braking-resistor are outside the port III of the ePSD.

Description

RELATED APPLICATIONS This application is a continuation-in-part of U.S. application Ser. No. 18/275,551, filed on Jan. 21, 2022, which is the U.S. National Stage of International Application No. PCT/CN2022/073181, filed on Jan. 21, 2022, which designates the U.S., published in Chinese and claims priority under 35 U.S.C. § 119 or 365 to Chinese Application No. 202110163841.4, filed on Feb. 5, 2021. The entire teachings of the above applications are incorporated herein by reference. TECHNICAL FIELD This application relates to a hybrid powertrain and a hybrid vehicle. BACKGROUND Road freight is critical to all major economies in the world. The long-haul freight truck (average working day runs more than 600 KM, more than 80% of the driving mileage is along a controlled-access expressway, the total vehicle weight exceeds 15 tons) is the core of the road freight industry. The long-haul heavy trucks are major sources of fuel consumption (CO2) and pollutant emissions (NOx) in the transportation industry. It is one of the key areas of the national government's annual energy conservation and emission reduction supervision. Today, Europe and the United States mandatory emission regulations on large commercial vehicles (with gross vehicle weight rating over 10 tons) including on-road heavy trucks (“heavy truck” for short) have moved from Euro-VI standard (effective in Europe since 2014) and US EPA-2010 (effective in USA since 2010) with emphasis on exhaust pollutant emissions reduction to a series of new emission standards with emphasis on the reduction of CO2 and other greenhouse-gas (GHG) emissions from the vehicle exhaust. The carbon emission (CO2 g/KM) of the vehicle is basically proportional to its fuel consumption (L/100 KM), therefore reducing the fuel consumption (or improving the fuel economy in MPG) is equivalent to reducing carbon emissions. The second phase of the greenhouse gas (GHG-II) for the medium/heavy engine (diesel or natural gas) and commercial vehicle promulgated by the US Federal Government in 2016 explicitly defines the period from 2021 to 2027, all the US newly registered medium/heavy engines and commercial vehicles, while maintaining the same EPA-2010 exhaust-gas pollutant emissions limits, must improve the vehicle fuel economy (FE, MPG or mile/gallon) year over year, equivalent to reducing fuel consumption (FC, L/100 KM) or carbon emission (CO2, g/KM), to meet detailed mandatory standards. In 2019, the EU passed the first mandatory regulation on heavy truck carbon emission in its history (that is, the European CO2 standard); under the premise of keeping the Euro-VI exhaust-gas pollutant emission limit unchanged, taking 2019 years diesel heavy truck carbon emission (fuel consumption) as the reference, requiring by 2025 European new heavy truck carbon emission (CO2, g/KM) to be reduced by 15%; by 2030, carbon emission to be reduced by 30%. China began to implement large commercial vehicle GB-5 mandatory emission regulations nationwide in 2017, and from July 2021, the country's national-GB-6 mandatory emission regulations have been implemented nationwide; The national GB-6 standard is basically the same as the European-VI standard and the US EPA-2010 standard at the exhaust-gas pollutant emissions limits, and some individual limits are even more stringent; At the same time, China also has regulations on heavy truck fuel consumption or carbon emission. The emission regulations are the most important driving forces for the development of powertrain technology in various countries in the world. The powertrain of China-GB-6 compliant heavy-trucks will be in the same technical platform for the first time in the history as the powertrain of the current North American and European heavy-trucks. According to the promulgation history of China-1 to GB-6 regulations over the past 20 years, China will likely follow the historical time-lines of EU-I to EU-VI regulations, and it is expected that China will follow EU, and soon launch new regulations focusing on carbon emission intensity and fuel consumption reduction. Obviously, after 2021, the mandatory emission regulations and industry focus of the three major markets in the world (China, the United States, and the United States) will continue to reduce the fuel consumption and carbon emissions of heavy-truck trucks by reducing the emissions of the heavy-truck exhaust-gas emissions. The average fuel cost of a trunk line is nearly 60 million US dollars per year in Europe and the United States, and the annual fuel cost of China is up to four hundred thousand RMB per year. The annual total oil cost of more than 2 million heavy trucks in the US exceeds 100 billion US dollars, and the total oil cost of more than 5 million heavy trucks in China is more than 10 billion RMB per year. Through technological innovation, the fuel consumption and emission of heavy truck are reduced, the main engine plant, driver, fleet, shipper, government, society and other interests ar