JP7408063B2 - Predictive power generation charging control method for range extender vehicles - Google Patents

Description

The present invention relates to a predictive power generation and charging control system installed in a range extender EV (Range Extended-Electrical Vehicle) vehicle that charges a secondary battery with an engine generator and drives a motor using the secondary battery.

EV vehicles powered by secondary batteries are attracting attention as a clean means of transportation that does not emit carbon dioxide (CO2). The first reason is that unlike vehicles that run on internal combustion engines, they run by driving motors using electricity stored in secondary batteries, so they emit no CO2, are quieter, and offer superior ride comfort. The second reason is that maintenance costs, including fuel costs, are lower than diesel engine vehicles, which is why it is considered to be a great advantage to introduce them.

However, the price of the current EV bus, which is a type of EV vehicle, depends on the modification of a bus equipped with a diesel engine, so it is necessary to install a large number of expensive secondary batteries. Compared to buses, the initial investment is several times more expensive, so their introduction has not progressed slowly. Furthermore, the widespread use of EV trucks has been delayed due to reasons such as the large amount of space for secondary batteries, which reduces the truck's loading capacity and makes them inconvenient to use.

Additionally, current secondary battery technology does not provide sufficient mileage and is not user-friendly due to long charging times. Although the adoption of ultra-fast charging technology that improves the charging time problem has been demonstrated, it is difficult to install charging equipment on routes, so bus operators and truck operators have no choice but to place it in locations where maintenance can be performed. There are problems with this, such as the time it takes to stop there to charge. Furthermore, since driver wages account for a large proportion of the expenses of bus and truck operators, charging time and time spent traveling to charge are wasted time and increase expenses. On the other hand, the development of next-generation secondary batteries with large charging capacity and short charging time is progressing, but there is currently no definitive solution, and we look forward to accelerating technological development.

As a prior art document, "Electric bus and charging system (Japanese Patent Application Laid-Open No. 2016-181965)" has been proposed. However, in this proposal, the charging timing of the secondary battery is determined by using the time when the passenger goes up and down, but since the time taken to go up and down is generally short, there is a risk that sufficient charging may not be possible.

As already mentioned, EVs require large-capacity batteries in order to maintain their driving range, which causes the problem of long charging times, but the series hybrid system is being applied to passenger cars as a solution to this problem. Generally, this technology uses an existing engine as a generator, is equipped with a small-capacity secondary battery, and almost always drives the engine to charge the secondary battery, and the secondary battery's power is used to power the motor. It is driven to move the vehicle. However, when applied to commercial vehicles such as buses and trucks, it is necessary to supply an excessive amount of instantaneous power required for steep uphill slopes, etc., which requires a large generator and a large amount of secondary batteries. As a result, series hybridization of commercial vehicles is extremely difficult because it takes up space, reduces the number of seats in buses, and limits the cargo capacity of trucks.

In contrast, the Range Extender EV (RE_EV) vehicle of this technology utilizes Geographic Information System (GIS) and GNSS (Global Navigation Satellite System) to collect position information on the driving route, altitude difference, etc. road surface information is being collected. Furthermore, by using the driving data accumulated during previous driving, a power generation plan (driving plan) is formulated before driving. By making a driving plan for the day before driving in this way, the required amount of power generation can be calculated in advance, which allows for appropriate power generation and charging, making it possible to downsize the generator and secondary battery. After the vehicle starts traveling, the vehicle can travel according to the plan by modifying the travel plan based on the travel data sequentially obtained during the travel. Additionally, if it is possible to perform external charging while driving, fuel efficiency can be further improved.

In this way, the present range extender vehicle drives the engine to charge the secondary battery only when the amount of charge in the secondary battery becomes low. Normally, the motor is driven only by the secondary battery without driving the engine, so there is no need to worry about running out of power while driving, unlike EV vehicles, and eliminates the limit on mileage that was an issue with EV vehicles. This makes it possible to make the vehicle extremely user-friendly. Furthermore, because this Range Extender EV vehicle runs on a motor powered by a secondary battery for a large portion of its driving time, it is a clean means of transportation that emits significantly less carbon dioxide than a regular engine-powered vehicle. Engine noise is limited, resulting in a quiet and comfortable ride for considerable driving time. Since maintenance costs, including fuel costs, are lower than diesel engine vehicles, it has been thought that there are great advantages to introducing them.

The proponent has previously proposed a patent applying such range extender technology to buses, which are one of the main vehicles in the public transportation system (Patent Application No. 2017-204209). This proposal allows even trucks that do not travel on a scheduled loop route, such as buses, to formulate a power generation plan before driving by using road surface information such as location information and altitude differences on the travel route. This makes range extender technology applicable to commercial vehicles.

As a prior art similar to this proposal, there is an "electric vehicle navigation system (Japanese Patent Laid-Open No. 8-240435) that detects map information, GPS information, and remaining battery capacity to control the drive of a generator installed in the vehicle. This proposal solves the problem of conventional hybrid cars, which emit exhaust gas even in non-polluting areas by driving the on-board generator when the battery capacity becomes low. This technology utilizes a navigation system that can run a generator to charge the vehicle when the battery is low, and in non-polluting areas, shut down the generator to prevent exhaust gas from being emitted. It is claimed that exhaust gas can be prevented as much as possible in pollution-free areas.However, the extender EV vehicle using the predictive power generation and charging control technology proposed in this proposal requires modeling and control methods to suppress the amount of power generation. By making full use of this system, it is possible to downsize the generator and use a small-capacity secondary battery without affecting the payload, making it possible to utilize so-called series hybrid technology in commercial vehicles as well.

Although the following description assumes that the engine is a small diesel engine, it is not limited to this, and may be a gasoline engine, a fuel generator (so-called fuel cell), or the like.

JP2016-181965 JP 8-240435

The problem to be solved by the present invention is that conventional series hybrid vehicles are equipped with a large number of secondary batteries and large generators in case of traveling on long steep slopes, so the number of seats in buses is limited, while the number of seats in trucks is limited. However, there was the issue of sacrificing cargo carrying capacity. Furthermore, engines for large power generators have had issues with fuel consumption and proportional CO2 reduction.

This proposal utilizes ICT such as GIS and GNSS before driving to obtain various information on the driving route and formulate a power generation plan before driving. This article describes a predictive power generation and charging control technology utilized in a range extender vehicle that can start and stop charging, making it possible to install a smaller engine generator and a smaller capacity secondary battery.
The previous prior art, JP-A-8-240435, focuses on stopping the engine only in that section in order to reduce exhaust gas in the non-polluting areas where the vehicle is traveling, so the driving route as proposed in this proposal is It does not take into account the overall driving conditions (for example, slopes, traffic congestion information, quiet sections, etc.).

In addition, in the previous proposal (Japanese Patent Application Laid-open No. 2016-181965), by taking advantage of the fact that the traveling route is fixed in the case of regularly operating buses, the drive and stop control of the generator can be controlled according to the traveling conditions and driving environment. It was controlled to be optimal. However, even if the destination changes daily, such as with a delivery truck, by extracting information on the route to the destination and various driving conditions before driving, it is possible to make a plan similar to that of a regularly scheduled bus. This makes it possible to drive with ease. As a result, in addition to reducing fuel consumption (reducing CO2 emissions), it becomes possible to drive with consideration to the local living environment, making it easier for both bus operators and truck delivery companies to introduce range extender vehicles.

In recent years, map information such as GIS can use not only horizontal position data but also elevation data. These are easily available via the Internet, and in Japan, the Geospatial Information Authority of Japan provides elevation data every 5 m, and this data is processed and used by the private sector to make it easier to use. It is expected that such services will expand overseas as well in the future. In this proposal, we created the energy model shown below using these data, and as a result of downsizing the system by controlling the generator, we have realized the application of range extender technology to commercial vehicles.

A travel route is regarded as a set of minute sections n, and these minute sections are defined as a unit section. If the power required to move a unit section is divided into the power Ph (n) required for horizontal movement and the power Pv (n) required for vertical movement, the total power Pn required for travel is as follows. .
_Destination
Pn = Σ(Ph(n) + Pv(n))
^{Point of departure}
Furthermore, if the average electricity cost per unit section of horizontal movement is C(n) and the distance is L(n), then the electric power required for each unit section of horizontal movement is as follows.

Ph(n) = L(n)/C(n)

Also, the power required for vertical movement can be calculated as follows.

P(v) = K(n)*m(n)*g*h(n)

Here, K is K(n)=+1 if the section is uphill, and K represents the regeneration coefficient when the section is downhill, and K(n) is negative. Also, g is the gravitational acceleration of 9.81m/S ² . From the above, the total power Pn required for running can be determined.

On the other hand, the electric power Ps required to cover the consumption of the vehicle's driving motor and auxiliary equipment while driving is the sum of the electric power Pi from external charging before driving and the electric power generated in the power generation section during driving, ΣPg(n). Become.

Ps＝Pi＋ΣPg(n)

Here, the generated power Pg(n) for unit section n is expressed as follows, assuming that the average speed of the section is SPD(n), the generator output is G (kW/h), and the section distance is L(n). be done.

Pg(n)＝G＊L(n)/SPD(n)

From these, it is possible to determine the electric power Ps that can be used while the vehicle is running. From the above, the condition for driving is Ps>Pn, and it is sufficient to create a power generation plan that takes into account the amount of electric power Pi for external charging so that this condition holds.

A power generation plan for when to generate the total generated power ΣPg(n) is created as follows. Utilize GIS to obtain elevation difference data for unit sections, and calculate distance L(n) for each unit section, average electricity cost for horizontal movement C(n), vehicle speed SPD(n), vehicle weight m(n), It is created as follows using the altitude difference h(n) and the regeneration coefficient k(n). The total amount of power generated ΣPg(n) required during driving can be obtained from the equations shown above as follows.

ΣPg(n)=Ps−Pi

This total power generation amount ΣPg(n) is determined by appropriately distributing the power generation amount (generated power x power generation section) over the driving route, taking into account quiet sections and regenerative power recovery sections, and how much power should be generated in which sections. do.

An appropriate method of distribution is to start power generation when the SOC (State of Charge) of the secondary battery reaches the lower limit, and stop the generator when it reaches the upper limit. Basically, the lower limit is the minimum value required to charge the secondary battery (10%, for example), and the upper limit is the highest allowable state of charge (90%, for example). In a basic driving plan, the SOC value is set to go back and forth between the minimum and maximum values of the secondary battery, but if there is a steep and long climb in the destination, a large amount of electric power is required. The engine is driven to start charging just before the lower limit is reached. In addition, if there is a steep, long downhill slope in the destination and a large amount of regenerated power is expected, the generator is stopped before the charger reaches its maximum charging limit and control is performed so that the regenerated power can be recovered without waste.

Figure 1 shows an example of the change in SOC, which indicates the state of charge of the secondary battery created in the travel plan, with respect to the travel distance. The vertical axis is SOC, and the horizontal axis is mileage. This shows the case where the secondary battery is fully charged before starting the journey. During section A at the beginning of the run, EV driving is performed with the generator stopped. It is possible to continue driving until the lower limit is reached, but since it is known that there are areas in front of the vehicle where the generator cannot be driven (for example, quiet sections such as hospital areas), drive the generator in section B. Charge the secondary battery. Since C is a quiet area, the generator is stopped. Since D has exceeded the quiet section, it will be charged, but there is a long steep downhill slope in section F, and a large amount of regenerated power is expected to be recovered, so the generator will be stopped before reaching the upper limit. E indicates the EV driving section, and F indicates the charging state of the secondary battery using regenerated power during a long downhill slope. Since I was able to charge up to the upper limit using the regenerated power, I am driving in EV mode in G, but since there is a steep uphill slope ahead (I area), I am generating electricity in section H. I has a steep uphill slope, so the SOC decrease rate is large. At the destination, the SOC (State of Charge) is planned to be at the lower limit, so power will be generated again in section J, and then the train will reach the final destination while driving on an EV.

As described above, the timing and section for starting and stopping the generator are created as a travel plan before driving, and the vehicle starts traveling in accordance with this plan. During actual driving, deviations (errors) from the driving plan may occur, so the driver uses information from GIS and GNSS to continually make corrections while driving. In the case of actual commercial operation, based on the delivery plan, the location information of the departure point and destination point, the route setting using the navigation system, the estimated arrival time, and the speed at each section during the route are taken into account. A travel plan is created.

Figure 2 shows the route the vehicle is scheduled to travel according to the travel plan, by obtaining position data and elevation data from GIS and GNSS for each unit section, and at the same time, the time of passage based on the distance L (n) and speed SPD (n) of the unit section. The image shows how to calculate the horizontal and vertical movement energy required for each unit distance by calculating Tps(n). The figure on the left is an image of calculating the horizontal movement energy of a vehicle. A curve generates rotational energy proportional to the radius r. The figure on the right is an image of finding the vertical movement energy.
This calculation of travel energy is also carried out while driving in order to verify that there are no major deviations from the original plan due to unanticipated traffic jams.

Figure 3 shows the control method of this system as a transition diagram. Start from the starting point and enter the generator stop circle on the left. If there is an item that satisfies the generation start conditions, it is moved to the right and the generator is driven. After that, if the generation stop conditions are met, the generator is stopped and moved to the left area. In this way, the generator is repeatedly stopped and driven, and when it reaches its destination, it exits the generator stop circle.

FIG. 4 shows a simplified flow chart of the control of this system. Before driving, information on the driving route from the current location to the destination is obtained from GIS and GNSS, and a driving plan is created taking into account the vehicle driving data (vehicle speed, electricity consumption, etc.) obtained from past driving records. do. After that, control starts according to the flowchart. First, it is determined whether the generator is started or stopped (normally it is stopped at the start of driving).

If it is stopped, follow the flow on the left. A value indicating the SOC power amount of the charger (Sc) and the lower limit of the SOC power amount (ScL) + the energy required to climb the slope in that section (α) + the energy required to pass through the quiet area Compare (q), and if Sc is greater, the generator continues traveling while stopped, and it is determined whether the end point has been reached. However, if the end point has not been reached, the system returns to the beginning of the flow and updates the travel plan by correcting any deviations from the travel plan using the vehicle speed, electricity consumption, SOC information, remaining battery power, etc. obtained during driving up to that point. It compares Sc with the required energy again, and if it determines that the remaining battery power is insufficient, it moves to the right side of the flow and starts charging with a generator.

On the other hand, if it is determined at the beginning of the flow that the generator is activated, the flow shifts to the right side. Here, if the remaining battery power (Sc) is greater than the upper limit of SOC power (ScH) - the regenerated energy in that section, the generator is stopped and the process moves to the flow on the left. However, if Sc is low, the vehicle continues driving with the generator running, but when it reaches a quiet section, the generator is stopped and the vehicle shifts to the left flow. Then, if it is not a quiet section, follow the flow, and if Sc is higher than the set battery level at the end point (destination), continue to follow the flow, drive the generator until the end point where Sc converges to the set value, and then After this point, the generator is stopped and the train heads towards the final point.

However, if it turns out that even if the generator is driven, the set point will not be reached at the end point, then the output of the generator will be increased and the flow will return to the upper level. As long as you drive according to the originally planned power generation, the Sc will converge to the set value at the end of the destination, but for example, if you use an auxiliary device (air conditioner, etc.) more than planned while driving, the battery level may drop to the planned value. In cases where the SOC decreases more than expected, the SOC may decrease more than expected.

5a and 5b show the situation (2) in FIG. 4. The lower limit value ScL of Sc and the set value ScT1 can be brought closer to the respective set values by stopping the generator at XL or XT1 while running. However, if the set value is ScT2, it is not possible to approach that value even if the generator is kept running, so the output of the generator is increased as in (2). Figure 5b shows where to stop the generator. In addition, (3) in the figure shows a situation where the vehicle can travel to the destination with initial charging before driving.

Figure 6 shows the input information, processing algorithm, and output information of predictive power generation and charging control using IT. As initial information, vehicle class information is obtained by inputting information such as the size and type of the vehicle only when this predictive power generation and charging control system device is first installed in the vehicle. After that, if the driving destination and route for that day have been determined, the driving route is entered, but if the driving route is not determined, this system presents the optimal route and other candidate routes, and the administrator or driver person can choose. Alternatively, it is also possible for the system to automatically determine the optimal route.

While driving, the current location, SOC, vehicle speed, operating status of the air conditioner, etc. are automatically input. Vehicle weight also affects fuel efficiency. Although the weight of the vehicle body itself is considered to be constant, the total weight of trucks changes as cargo is loaded and unloaded, and the total weight of buses changes as passengers board and disembark. For this reason, it is necessary to determine the fluctuation in the total weight while the vehicle is running. For example, in a truck, the power consumption of the drive motor is monitored, and the change in potential energy can be obtained from the difference between the power consumed in a certain section of flat ground and the power consumed in a certain section with a difference in height, so from the formula for potential energy (m x g x h) Find the weight m. Alternatively, if the weight of the vehicle without cargo or passengers is known, the total weight can be determined from the degree of deterioration of fuel efficiency when carrying cargo or passengers. Furthermore, in the case of a bus, the number of passengers can be determined from the number of passengers getting on and off the bus, so if the average weight is assumed, the weight change can be determined within an allowable error.

Next, the processing algorithm section formulates a power generation and charging plan by understanding the route and calculating the amount of electricity required to reach the destination. Furthermore, the output information includes generator start and stop instruction information, as well as driving information for each vehicle for the driver and vehicle headquarters (control center, etc.) such as driving position, speed, SOC, engine operating status, and purpose. It provides information such as predicted driving conditions to the destination, changes in vehicle interior temperature, and changes in total vehicle weight.

Figure 7 shows a vehicle equipped with a predictive power generation/charging control system and the vehicle headquarters (bus center for buses, control facility for trucks, etc.), which is a ground-side system that monitors each vehicle and gives instructions on how to deal with problems. ) is the main schematic diagram. It also shows charging systems (CHAdeMO quick chargers, etc.) installed at appropriate locations along the driving route.

In the figure, 100 indicates the overall configuration of a range extender (RE-EV) vehicle, and 101 is a block containing only the electric drive unit, which mainly includes an EV motor inverter block 102 that drives the vehicle, an EV drive battery 103, and an EV It is composed of a control device 104 and the like. Furthermore, 105 is a communication device for communicating with a ground system, and 106 is a GNSS (Global Navigation Satellite System) position information device. Reference numeral 107 is the predictive power generation and charging control device itself, which has the role of obtaining position information etc. from GIS and GNSS and outputting instructions to the power generation unit 108 to start and stop power generation. In addition, 109 is a charging system (CHAdeMO quick charger, etc.) installed on the driving route, and if you have a certain amount of time such as a break time, you can also charge from outside, so the operating time of the generator will be longer. This makes it possible to reduce fuel consumption and CO2 emissions accordingly.

FIG. 8 shows an algorithm (200) of predictive power generation and charging control technology. This system uses GNSS position information 201 and map information from GIS 202 to obtain the current position of the vehicle on the driving route. Furthermore, information such as the SOC, vehicle speed, electric power required for air conditioning, outside temperature, and changes in vehicle weight, which is the vehicle running state, is acquired from the vehicle body 203 . From the information in 202 and 203, in 205 the amount of power required for horizontal movement to the destination is calculated. Further, in 206, the amount of electric power converted from the potential energy for vertically lifting the vehicle on a slope, etc. and the recovered power recovered on the way down the slope are calculated, and in 207, the remaining amount of the secondary battery is calculated. From these three pieces of information in 205, 206, and 207, in 208, the amount of power required to reach the destination is extracted in real time (specifically, the planned power generation amount and the timing of starting and stopping the power generation are calculated). Upon receiving this information, the RE power generation unit control signal generator 209 instructs the RE power generation unit 210 to generate and stop power generation. Reference numeral 211 indicates an on-vehicle computer that implements these algorithms.

Next, an overview of the operation of the predictive power generation and charging control technology will be shown using FIGS. 9a, 9b, and 9c. The numbers on the left side of each figure correspond to the numbers on the right side. 10 shows a cross-sectional view of the driving route (route A), where the vertical axis shows altitude and the horizontal axis shows distance. 11 is a flat road, 12 is an uphill road, 13 is a short flat road, 14 is a downhill road, and 15 is a flat road to the end point. Here, it is assumed that the vehicle maintains a constant speed no matter where it travels. 20 can be converted into power consumption (kW) on the vertical axis and time on the horizontal axis, assuming that the speed of the vehicle is constant everywhere on the road. Note that 12 and 14 are sloped roads, so the drawings take into account the fact that the distances are longer than those on flat roads. Here, if the power consumption on the flat roads 11, 13, and 15 is a, the power consumption on the uphill slope 12 is b, and the regenerated power on the downhill slope 14 is c, then the area of the square below the dashed line is the area of each running path. The amount of electricity consumed (kWh) in The areas of 21, 22, 23, and 25 represented by triangles with the same area also represent the amount of power consumed. Furthermore, since power is regenerated when going downhill, the amount of power generated is 24.

30 shows the change in the remaining power level (SOC) of the battery. Initially, the SOC was A, but as the vehicle consumes electricity while driving, the SOC gradually decreases. The triangle (21) drawn by traveling from A to B is similar to the power consumption 21 of the same traveling route in Figure 20 above, so it is expressed by the same area for simplicity. Similarly, if we transfer the power consumption shown by the triangles of the other travel routes in Figure 20 above to the SOC graph, 22 will become (22), 23 will become (23), 25 will become (25), and the regenerated power amount 24 becomes (24), so as a result, a graph of changes in SOC can be drawn. In the example of No. 30, the SOC becomes F at the final point, which is the lower limit of the SOC, and the vehicle can travel with only the initial charge amount, making it the most efficient example.

40 in FIG. 9b is an example of A' where the amount of charge before driving is smaller than that in FIG. 30 above. The change in SOC is the same as in the case of 30, but since the SOC will fall below the SOC lower limit between B' and C' while driving, it is expected that if this continues, the car will run out of electricity and will not be able to run. Therefore, in order to make F' become F'', B' should be made to become B'' (B''-B'= F''-F'), and the insufficient amount of electricity is at the SOC lower limit. Since it is the sum of the areas of each triangle below, the power shortage P4 is the formula P1+P2+P3-Pg, which is the sum of P1, P2, and P3 minus Pg. Note that Pg is the regenerated electric energy. By generating electric power P4 equal to the electric power shortage in advance, the vehicle can run without running out of power.

50 shows a case where the power generation output of the generator is d, and power generation is started from T1 so that P5=P4. 60 has a stronger generator output e than the example of 50, so power generation starts at T2 later than T1.

70 shows a case where there is a hospital etc. in the middle of driving route 11 and the generator is required to be stopped in that section as it is a quiet section, so power generation is divided into P7 and P8 (P7+P8= P6). 80, the output of the generator is strong, and if the increase ratio R2 of P9 is larger than the SOC decrease ratio R1 of P1, it is sufficient to start power generation before T5 when the SOC does not fall below the SOC lower limit, so power generation will start. The degree of freedom expands. In this example, in the case of P9, power generation starts at T5, just before the SOC lower limit falls, but this indicates that power generation can be started even before T5, as in P10 or P11.

Further, 90 in FIG. 9c shows an example in which a change in the travel route (route B) occurs during the travel of 10. If the driving route changes at point X and the driving route changes to 11', 12', or 13', it is necessary to immediately re-predict the change in SOC on the new driving route. The flat road has been changed from 10 to 11', but as shown in 100, the power consumption a remains the same, so the power consumption in 21 has been changed to the area of the triangle 31. 12' is a steep uphill slope, so the power consumption increases significantly and becomes c. Therefore, the amount of power consumed is the area of 32 triangles. After going uphill, the road is flat until the end, so the power consumption is 33.

On the other hand, as shown at 110, the change in SOC was (21) before the change in the driving route, but it changes to (31) due to the route change. After that, the SOC drops rapidly due to the steep uphill slope, and falls below the SOC lower limit halfway from I to J. In order to avoid this situation, it is necessary to correct the power generation plan immediately at point X when the vehicle recognizes the change in the driving route. The insufficient power consumption is P12+P13, which is the sum of the power consumption below the SOC lower limit, and the sum P14 can be calculated.

120 is a case where the generator output is f, and even if power generation is started at T6, which is later than X, the generated power amount P15 can be made equal to the insufficient power amount P14, so the vehicle can run. However, in the case of 130, since the generator output g is low, in order to obtain the generated power amount P16 equal to the power shortage amount P14, it was necessary to start power generation at T7, which has already passed. Therefore, in order to avoid power shortages after this, it is necessary to increase the output of the generator, stop at a charging station to recharge, or choose a different driving route.

In this way, predictive power generation and charging control is a technology that allows you to create a travel plan (power generation plan) in advance by using GNSS and GIS, which is a type of ICT technology, to obtain information on the driving route before departure. . Furthermore, this technology enables efficient driving by constantly updating the power generation plan based on the latest information from GNSS and GIS while driving. Next, we will describe the operation of the predictive power generation control technology in more detail.

FIG. 10 shows more specifically how the predictive power generation and charging control is performed while the vehicle is running. In this example, the speed of the vehicle on a flat road and on a slope is changed. Further, the distance of a slope that is longer than the horizontal distance by the slope is not taken into consideration because the slope on the actual road is considered to be much smaller than in this drawing. Here, the upper figure represents a topographic map, and the lower figure represents an electric power map. Also, the horizontal axis in the above diagram shows distance, but by considering the speed while driving, the horizontal axis in the bottom diagram can be converted to a time axis. Each line in the figure below represents the following. A represents how the SOC value before driving increases due to power generation while driving, B represents the change in SOC while driving, and C represents the increase in power consumption due to driving. It shows the total amount of power consumed.

Here, the value obtained by subtracting C from A is expressed as the change in SOC of B. Furthermore, the amount of power consumed while C is running is considered to be 1 consumption per unit time on a flat road 11, and 2 consumption per unit time on an uphill slope 12. Furthermore, in this example, regenerative power is not included because it is assumed that one power is consumed per unit time even when going downhill 14. When the SOC decreases due to power consumption during driving and reaches a predetermined value (4kW in this example), the generator is activated to start charging the secondary battery. Assuming that the power generation amount at this time is 3 power generation per unit time, it is more than 2 power consumption per unit time on uphill slope 12, so SOC is increasing, and the timing to stop power generation is when SOC reaches the upper limit. be. However, if it is determined that the amount of power generation is too low to recover the SOC on an uphill slope, the power generation start time of the generator is further brought forward and the amount of power of the secondary battery is increased.

In this way, by dividing the driving route into each small section and obtaining driving route information at the divided points from GIS and GNSS, driving plans (power generation plans) can be made in advance, and altitude information can be obtained in real time while driving. By obtaining vehicle position information from GIS and GNSS, it is possible to optimally control power generation and charging.

Figure 11a is a cross-sectional view of the driving route used to perform the SOC simulation for the route from Tokyo to Numazu over Hakone Pass, with and without predictive power generation/charging control. The horizontal axis shows the distance traveled and the vertical axis shows the altitude. Further, in FIG. 11b, the horizontal axis indicates the location (a, b, etc.) of each traveling point on FIG. 11a, and the vertical axis indicates the SOC. Starting from Tokyo, the EV travels on a mostly flat area for a while, but as it enters Hakone and approaches the Hakone Pass, the altitude increases rapidly, causing the battery's charge to decrease significantly. The situation is shown in parts e to f of Fig. 11b, where the SOC rapidly decreases. However, when predictive power generation/charging control is used, the amount of power required to cross a mountain pass can be calculated when formulating a power generation plan before driving, so the amount of power required to cross a mountain pass can be calculated at the time when the SOC reaches the lower limit (10% in this example). By starting power generation at the point, the battery can be charged with enough power to travel through Hakone Pass without any problems. However, if predictive power generation/charging control is not used, power generation will start when the SOC reaches the lower limit, and the battery will not be able to store enough power, and during a climb up Hakone Pass (e You can see that the power will run out between (and f).

Of course, if it is equipped with a battery that can charge a sufficient amount of battery power and a powerful generator, it is possible to drive without using predictive power generation and charging control technology, but in that case, there are many problems as mentioned above. can occur. First, a large number of batteries and large generators take up space and weight, which affects the interior space of buses and reduces the carrying capacity of trucks. Furthermore, there are concerns that fuel efficiency will worsen due to the increased weight, and the advantages of range extender EV vehicles, such as low fuel consumption and associated low CO2 emissions, will be spoiled, and there are concerns that the vehicle will become unattractive. .

The present invention incorporates a device that incorporates predictive power generation and charging control technology into a so-called range extender EV vehicle that is equipped with a generator to charge the battery as needed in an EV vehicle that runs with a motor driven by a battery. By installing a small battery and a small generator, it is possible to reduce fuel consumption and CO2 emissions without sacrificing the passenger space of a bus or the cargo space of a truck. This is a technology that helps improve the environment. Furthermore, if applied to distribution systems that support public transportation and social infrastructure, it will be possible to reduce fuel consumption and at the same time reduce CO2 emissions, which will have a significant effect on the realization of a low-carbon society.

An example of how the state of charge (SOC) of a secondary battery changes depending on the mileage An image diagram that calculates the energy required for movement by acquiring position data and elevation data for each unit section Transition diagram of predictive power generation and charging control Flowchart of predictive power generation and charging control Condition in which the generator approaches the end point while starting Point where the generator is turned off when SOC becomes ScT at the end point (X) Input/output information and processing algorithm of predictive power generation and charging control system Relationship between predictive power generation and charging control and main blocks Processing overview of predictive power generation and charging control algorithm Outline diagram of predictive power generation and charging control (1) Overview diagram of predictive power generation and charging control (2) Overview diagram of predictive power generation and charging control (3) Detailed explanation diagram of predictive power generation and charging control Driving route from Tokyo to Numazu SOC status when using and not using predictive power generation and charging control technology

Claims (9)

By setting the destination and/or driving route before driving, you can preset the point and/or time at which the generator will start charging and stop charging while driving.
The driving route is regarded as a collection of minute sections, and these minute sections are considered as unit sections, and the power required to travel the unit section is calculated by dividing the power required for horizontal movement and the power required for vertical movement. Determine the total power required for running,
Even while driving, altitude information is obtained from the Geographic Information System (GIS) and global positioning information from the Global Positioning Satellite System (GNSS) in real time.Based on these, each unit distance, unit time, or unit Starts or stops charging the generator in real time by incorporating the traveling speed at the traveling point, remaining battery power, operating status of auxiliary equipment, and fluctuations in the total vehicle weight while traveling for each unit that combines distance and unit time. reviewed,
The above-mentioned fluctuation in the total vehicle weight is due to the loading and unloading of cargo, or the boarding and disembarkation of passengers . Predictive power generation and charging control technology for extender vehicles.
Regarding claim 1, the information on the destination and driving route is obtained by utilizing Geographic Information System (GIS) and Global Navigation Satellite System (GNSS),
Using position information from the Global Navigation Satellite System (GNSS) and map information from the Geographic Information System (GIS), the current position of the vehicle on the driving route is acquired, and the SOC, which is the vehicle's driving status, is acquired from the vehicle itself. Obtains information on vehicle speed, power required for air conditioning, outside temperature, and changes in vehicle weight, and uses this information to calculate the amount of power required to move horizontally to the destination and the potential energy required to lift the vehicle vertically on a slope. A prediction for a range extender vehicle that calculates the amount of electricity converted from , the electricity collected on the way down the hill, and the remaining amount of secondary battery, and extracts the amount of electricity required to reach the destination in real time. Power generation charging control technology.
Regarding claim 1, the generated power Pg(n) in a unit section n, which is specified from the point or time of charging start and charging stop of the generator during driving, or both, is calculated by calculating the average speed of the power generation section by SPD(n), When the generator output is G (kW/h) and the section distance is L (n), the following formula,
Pg(n)＝G＊L(n)/SPD(n)
Predictive power generation and charging control technology for range extender vehicles, which is characterized by calculation.
In relation to claim 1, the driving situation where the battery consumption is estimated to be high at the driving destination is predicted in advance, and the charging of the generator is started before the lower limit of the secondary battery is reached, and the charging is started before the lower limit value of the secondary battery is reached, and the regeneration is carried out at the driving destination. A predictive power generation/charging control technology for a range extender vehicle that predicts that a large amount of electric power will be generated and stops charging the generator before the upper limit of the secondary battery is reached.
2. A predictive power generation/charging control technology for a range extender vehicle according to claim 1, which increases the output of the generator if it is determined that the set value will not be reached at the end point even if the generator is driven.
Regarding claim 1, if the average electricity cost of a unit section of horizontal movement is C(n) and the distance is L(n),
The power Ph(n) per unit area required for horizontal movement is calculated by the following formula,
Ph(n)＝C(n)＊L(n)
The power Pv(n) required for vertical movement is calculated by the following formula,
Pv(n)＝K(n)＊m(n)＊g＊h(n)
(Here, K is K(n) = +1 if the section is uphill, and K is the regeneration coefficient and k(n) is negative if the section is downhill. Also, m(n) is the vehicle weight, and g is the gravitational acceleration. 9.8m/s ² , h(n) is the altitude difference)
Predictive power generation charging control technology for range extender vehicles .
According to claim 1, there is provided a range extender vehicle characterized in that the start and stop of the generator is controlled in consideration of the power generation output of the generator so that the remaining capacity of the battery reaches a predetermined value at the destination. Predictive power generation and charging control technology.
Regarding claim 7 , if the remaining capacity of the battery is expected to be lower than a predetermined value at the destination, the period and driving location for generating the amount of electricity expected to be insufficient will be changed to the destination. Predictive power generation/charging control technology for range extender vehicles, which features a surplus during driving.
Regarding claim 2, if the destination or driving route is changed during the trip, the information on the changed destination and driving route can be obtained from GIS and GNSS to start charging the generator and A predictive power generation/charging control technology for range extender vehicles that is characterized by resetting the stopping point or timing, or both.